huffman codingfrom wikipedia the free encyclopediathis article includes a list of references but its sources remain unclear because it has insufficient inline citations please help to improve this article by introducing more precise citations january huffman tree generated from the exact frequencies of the text this is an example of a huffman tree the frequencies and codes of each character are below encoding the sentence with this code requires  bits as opposed to  or  bits if  characters of  or  bits were used this assumes that the code tree structure is known to the decoder and thus does not need to be counted as part of the transmitted informationchar freq codespace  a  e  f  h  i  m  n  s  t  l  o  p  r  u  x  in computer science and information theory a huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression the process of finding andor using such a code proceeds by means of huffman coding an algorithm developed by david a huffman while he was a phd student at mit and published in the  paper a method for the construction of minimumredundancy codesthe output from huffmans algorithm can be viewed as a variablelength code table for encoding a source symbol such as a character in a file the algorithm derives this table from the estimated probability or frequency of occurrence weight for each possible value of the source symbol as in other entropy encoding methods more common symbols are generally represented using fewer bits than less common symbols huffmans method can be efficiently implemented finding a code in linear time to the number of input weights if these weights are sorted however although optimal among methods encoding symbols separately huffman coding is not always optimal among all compression methodscontents     history     terminology     problem definition         informal description         formalized description         example     basic technique         compression         decompression     main properties         optimality     variations         nary huffman coding         adaptive huffman coding         huffman template algorithm         lengthlimited huffman codingminimum variance huffman coding         huffman coding with unequal letter costs         optimal alphabetic binary trees hutucker coding         the canonical huffman code     applications     see also     notes     referenceshistoryin  david a huffman and his mit information theory classmates were given the choice of a term paper or a final exam the professor robert m fano assigned a term paper on the problem of finding the most efficient binary code huffman unable to prove any codes were the most efficient was about to give up and start studying for the final when he hit upon the idea of using a frequencysorted binary tree and quickly proved this method the most efficientin doing so the student outdid his professor who had worked with information theory inventor claude shannon to develop a similar code by building the tree from the bottom up instead of the top down huffman avoided the major flaw of the suboptimal shannonfano codingterminologyhuffman coding uses a specific method for choosing the representation for each symbol resulting in a prefix code sometimes called prefixfree codes that is the bit string representing some particular symbol is never a prefix of the bit string representing any other symbol huffman coding is such a widespread method for creating prefix codes that the term huffman code is widely used as a synonym for prefix code even when such a code is not produced by huffmans algorithmproblem definitionconstructing a huffman treeinformal descriptiongiven    a set of symbols and their weights usually proportional to probabilitiesfind    a prefixfree binary code a set of codewords with minimum expected codeword length equivalently a tree with minimum weighted path length from the rootformalized descriptioninputalphabet a  leftaacdotsanright which is the symbol alphabet of size nset w  leftwwcdotswnright which is the set of the positive symbol weights usually proportional to probabilities ie wi  mathrmweightleftairight leq i leq noutputcode c leftawright  leftcccdotscnright which is the set of binary codewords where ci is the codeword for ai  leq i leq ngoallet lleftcright  suminwitimesmathrmlengthleftciright be the weighted path length of code c condition lleftcright leq llefttright for any code tleftawrightexamplewe give an example of the result of huffman coding for a code with five words and given weights we will not verify that it minimizes l over all codes it does of course but we will compute l and compare it to the shannon entropy h of the given set of weights the result is nearly optimalinput a w symbol ai a b c d e sumweights wi       output c codewords ci       codeword length in bitsli     contribution to weighted path lengthli wi       lc  optimality probability budgetli       information content in bitslog wi        contribution to entropywi log wi      ha  for any code that is biunique meaning that the code is uniquely decodeable the sum of the probability budgets across all symbols is always less than or equal to one in this example the sum is strictly equal to one as a result the code is termed a complete code if this is not the case you can always derive an equivalent code by adding extra symbols with associated null probabilities to make the code complete while keeping it biuniqueas defined by shannon  the information content h in bits of each symbol ai with nonnull probability is    hai  log over wi the entropy h in bits is the weighted sum across all symbols ai with nonzero probability wi of the information content of each symbol    ha  sumwi   wi hai  sumwi   wi log over wi   sumwi   wi logwi note a symbol with zero probability has zero contribution to the entropy since limw to  w log w   so for simplicity symbols with zero probability can be left out of the formula aboveas a consequence of shannons source coding theorem the entropy is a measure of the smallest codeword length that is theoretically possible for the given alphabet with associated weights in this example the weighted average codeword length is  bits per symbol only slightly larger than the calculated entropy of  bits per symbol so not only is this code optimal in the sense that no other feasible code performs better but it is very close to the theoretical limit established by shannonin general a huffman code need not be unique thus the set of huffman codes for a given probability distribution is a nonempty subset of the codes minimizing lc for that probability distribution however for each minimizing codeword length assignment there exists at least one huffman code with those lengthsbasic techniquecompressiona source generates  different symbols a  a  a  a  with probability         a binary tree is generated from left to right taking the two least probable symbols and putting them together to form another equivalent symbol having a probability that equals the sum of the two symbols the process is repeated until there is just one symbol the tree can then be read backwards from right to left assigning different bits to different branches the final huffman code issymbol codea a a a the standard way to represent a signal made of  symbols is by using  bitssymbol but the entropy of the source is  bitssymbol if this huffman code is used to represent the signal then the average length is lowered to  bitssymbol it is still far from the theoretical limit because the probabilities of the symbols are different from negative powers of twothe technique works by creating a binary tree of nodes these can be stored in a regular array the size of which depends on the number of symbols n a node can be either a leaf node or an internal node initially all nodes are leaf nodes which contain the symbol itself the weight frequency of appearance of the symbol and optionally a link to a parent node which makes it easy to read the code in reverse starting from a leaf node internal nodes contain symbol weight links to two child nodes and the optional link to a parent node as a common convention bit  represents following the left child and bit  represents following the right child a finished tree has up to n leaf nodes and n internal nodes a huffman tree that omits unused symbols produces the most optimal code lengthsthe process essentially begins with the leaf nodes containing the probabilities of the symbol they represent then a new node whose children are the  nodes with smallest probability is created such that the new nodes probability is equal to the sum of the childrens probability with the previous  nodes merged into one node thus not considering them anymore and with the new node being now considered the procedure is repeated until only one node remains the huffman treethe simplest construction algorithm uses a priority queue where the node with lowest probability is given highest priority    create a leaf node for each symbol and add it to the priority queue    while there is more than one node in the queue        remove the two nodes of highest priority lowest probability from the queue        create a new internal node with these two nodes as children and with probability equal to the sum of the two nodes probabilities        add the new node to the queue    the remaining node is the root node and the tree is completesince efficient priority queue data structures require olog n time per insertion and a tree with n leaves has n nodes this algorithm operates in on log n time where n is the number of symbolsif the symbols are sorted by probability there is a lineartime on method to create a huffman tree using two queues the first one containing the initial weights along with pointers to the associated leaves and combined weights along with pointers to the trees being put in the back of the second queue this assures that the lowest weight is always kept at the front of one of the two queues    start with as many leaves as there are symbols    enqueue all leaf nodes into the first queue by probability in increasing order so that the least likely item is in the head of the queue    while there is more than one node in the queues        dequeue the two nodes with the lowest weight by examining the fronts of both queues        create a new internal node with the two justremoved nodes as children either node can be either child and the sum of their weights as the new weight        enqueue the new node into the rear of the second queue    the remaining node is the root node the tree has now been generatedalthough lineartime given sorted input in the general case of arbitrary input using this algorithm requires presorting thus since sorting takes on log n time in the general case both methods have the same overall complexityin many cases time complexity is not very important in the choice of algorithm here since n here is the number of symbols in the alphabet which is typically a very small number compared to the length of the message to be encoded whereas complexity analysis concerns the behavior when n grows to be very largeit is generally beneficial to minimize the variance of codeword length for example a communication buffer receiving huffmanencoded data may need to be larger to deal with especially long symbols if the tree is especially unbalanced to minimize variance simply break ties between queues by choosing the item in the first queue this modification will retain the mathematical optimality of the huffman coding while both minimizing variance and minimizing the length of the longest character codeheres an example of optimized huffman coding using the french subject string jaime aller sur le bord de leau les jeudis ou les jours impairs note that the original huffman coding tree structure would be different from the given examplehuffman huff demogifdecompressiongenerally speaking the process of decompression is simply a matter of translating the stream of prefix codes to individual byte values usually by traversing the huffman tree node by node as each bit is read from the input stream reaching a leaf node necessarily terminates the search for that particular byte value before this can take place however the huffman tree must be somehow reconstructed in the simplest case where character frequencies are fairly predictable the tree can be preconstructed and even statistically adjusted on each compression cycle and thus reused every time at the expense of at least some measure of compression efficiency otherwise the information to reconstruct the tree must be sent a priori a naive approach might be to prepend the frequency count of each character to the compression stream unfortunately the overhead in such a case could amount to several kilobytes so this method has little practical use if the data is compressed using canonical encoding the compression model can be precisely reconstructed with just bb bits of information where b is the number of bits per symbol another method is to simply prepend the huffman tree bit by bit to the output stream for example assuming that the value of  represents a parent node and  a leaf node whenever the latter is encountered the tree building routine simply reads the next  bits to determine the character value of that particular leaf the process continues recursively until the last leaf node is reached at that point the huffman tree will thus be faithfully reconstructed the overhead using such a method ranges from roughly  to  bytes assuming an bit alphabet many other techniques are possible as well in any case since the compressed data can include unused trailing bits the decompressor must be able to determine when to stop producing output this can be accomplished by either transmitting the length of the decompressed data along with the compression model or by defining a special code symbol to signify the end of input the latter method can adversely affect code length optimality howevermain propertiesthe probabilities used can be generic ones for the application domain that are based on average experience or they can be the actual frequencies found in the text being compressed this requires that a frequency table must be stored with the compressed text see the decompression section above for more information about the various techniques employed for this purposeoptimalityalthough huffmans original algorithm is optimal for a symbolbysymbol coding ie a stream of unrelated symbols with a known input probability distribution it is not optimal when the symbolbysymbol restriction is dropped or when the probability mass functions are unknown also if symbols are not independent and identically distributed a single code may be insufficient for optimality other methods such as arithmetic coding and lzw coding often have better compression capability both of these methods can combine an arbitrary number of symbols for more efficient coding and generally adapt to the actual input statistics useful when input probabilities are not precisely known or vary significantly within the stream however these methods have higher computational complexity also both arithmetic coding and lzw were historically a subject of some concern over patent issues however as of mid the most commonly used techniques for these alternatives to huffman coding have passed into the public domain as the early patents have expiredhowever the limitations of huffman coding should not be overstated it can be used adaptively accommodating unknown changing or contextdependent probabilities in the case of known independent and identically distributed random variables combining symbols blocking reduces inefficiency in a way that approaches optimality as the number of symbols combined increases huffman coding is optimal when each input symbol is a known independent and identically distributed random variable having a probability that is an the inverse of a power of twoprefix codes tend to have inefficiency on small alphabets where probabilities often fall between these optimal points the worst case for huffman coding can happen when the probability of a symbol exceeds    making the upper limit of inefficiency unbounded these situations often respond well to a form of blocking called runlength encoding for the simple case of bernoulli processes golomb coding is a provably optimal runlength codefor a set of symbols with a uniform probability distribution and a number of members which is a power of two huffman coding is equivalent to simple binary block encoding eg ascii coding this reflects the fact that compression is not possible with such an inputvariationsmany variations of huffman coding exist some of which use a huffmanlike algorithm and others of which find optimal prefix codes while for example putting different restrictions on the output note that in the latter case the method need not be huffmanlike and indeed need not even be polynomial time an exhaustive list of papers on huffman coding and its variations is given by code and parse trees for lossless source encodingnary huffman codingthe nary huffman algorithm uses the     n   alphabet to encode message and build an nary tree this approach was considered by huffman in his original paper the same algorithm applies as for binary n equals  codes except that the n least probable symbols are taken together instead of just the  least probable note that for n greater than  not all sets of source words can properly form an nary tree for huffman coding in this case additional probability place holders must be added this is because the tree must form an n to  contractor for binary coding this is a  to  contractor and any sized set can form such a contractor if the number of source words is congruent to  modulo n then the set of source words will form a proper huffman treeadaptive huffman codinga variation called adaptive huffman coding involves calculating the probabilities dynamically based on recent actual frequencies in the sequence of source symbols and changing the coding tree structure to match the updated probability estimates it is used rarely in practice since the cost of updating the tree makes it slower than optimized adaptive arithmetic coding that is more flexible and has a better compressionhuffman template algorithmmost often the weights used in implementations of huffman coding represent numeric probabilities but the algorithm given above does not require this it requires only that the weights form a totally ordered commutative monoid meaning a way to order weights and to add them the huffman template algorithm enables one to use any kind of weights costs frequencies pairs of weights nonnumerical weights and one of many combining methods not just addition such algorithms can solve other minimization problems such as minimizing maxileftwimathrmlengthleftcirightright a problem first applied to circuit designlengthlimited huffman codingminimum variance huffman codinglengthlimited huffman coding is a variant where the goal is still to achieve a minimum weighted path length but there is an additional restriction that the length of each codeword must be less than a given constant the packagemerge algorithm solves this problem with a simple greedy approach very similar to that used by huffmans algorithm its time complexity is onl where l is the maximum length of a codeword no algorithm is known to solve this problem in linear or linearithmic time unlike the presorted and unsorted conventional huffman problems respectivelyhuffman coding with unequal letter costsin the standard huffman coding problem it is assumed that each symbol in the set that the code words are constructed from has an equal cost to transmit a code word whose length is n digits will always have a cost of n no matter how many of those digits are s how many are s etc when working under this assumption minimizing the total cost of the message and minimizing the total number of digits are the same thinghuffman coding with unequal letter costs is the generalization without this assumption the letters of the encoding alphabet may have nonuniform lengths due to characteristics of the transmission medium an example is the encoding alphabet of morse code where a dash takes longer to send than a dot and therefore the cost of a dash in transmission time is higher the goal is still to minimize the weighted average codeword length but it is no longer sufficient just to minimize the number of symbols used by the message no algorithm is known to solve this in the same manner or with the same efficiency as conventional huffman codingoptimal alphabetic binary trees hutucker codingin the standard huffman coding problem it is assumed that any codeword can correspond to any input symbol in the alphabetic version the alphabetic order of inputs and outputs must be identical thus for example a  leftabcright could not be assigned code hleftacright  leftright but instead should be assigned either hleftacright leftright or hleftacright  leftright this is also known as the hutucker problem after t c hu and alan tucker the authors of the paper presenting the first linearithmic solution to this optimal binary alphabetic problem which has some similarities to huffman algorithm but is not a variation of this algorithm these optimal alphabetic binary trees are often used as binary search treesthe canonical huffman codeif weights corresponding to the alphabetically ordered inputs are in numerical order the huffman code has the same lengths as the optimal alphabetic code which can be found from calculating these lengths rendering hutucker coding unnecessary the code resulting from numerically reordered input is sometimes called the canonical huffman code and is often the code used in practice due to ease of encodingdecoding the technique for finding this code is sometimes called huffmanshannonfano coding since it is optimal like huffman coding but alphabetic in weight probability like shannonfano coding the huffmanshannonfano code corresponding to the example is  which having the same codeword lengths as the original solution is also optimal but in canonical huffman code the result is applicationsarithmetic coding can be viewed as a generalization of huffman coding in the sense that they produce the same output when every symbol has a probability of the form k in particular it tends to offer significantly better compression for small alphabet sizes huffman coding nevertheless remains in wide use because of its simplicity and high speed intuitively arithmetic coding can offer better compression than huffman coding because its code words can have effectively noninteger bit lengths whereas code words in huffman coding can only have an integer number of bits therefore there is an inefficiency in huffman coding where a code word of length k only optimally matches a symbol of probability k and other probabilities are not represented as optimally whereas the code word length in arithmetic coding can be made to exactly match the true probability of the symbolhuffman coding today is often used as a backend to some other compression methods deflate pkzips algorithm and multimedia codecs such as jpeg and mp have a frontend model and quantization followed by huffman coding or variablelength prefixfree codes with a similar structure although perhaps not necessarily designed by using huffmans algorithmclarification neededsee also    adaptive huffman coding    data compression    group  compression    huffyuv    lempelzivwelch    modified huffman coding  used in fax machines    shannonfano coding    varicodenoteswikimedia commons has media related to huffman coding    huffman d  a method for the construction of minimumredundancy codes pdf proceedings of the ire    doijrproc edit    van leeuwen jan  on the construction of huffman trees pdf icalp  retrieved  february     see ken huffman     hu t c tucker a c  optimal computer search trees and variablelength alphabetical codes siam journal on applied mathematics    doi jstor  editreferences    da huffman a method for the construction of minimumredundancy codes proceedings of the ire september  pp  huffmans original article    ken huffman profile david a huffman scientific american september  pp     thomas h cormen charles e leiserson ronald l rivest and clifford stein introduction to algorithms second edition mit press and mcgrawhill  isbn  section  pp hide    v    t    edata compression methodslossless entropy type     unary    arithmetic    golomb    huffman        adaptive        canonical        modified    range    shannon    shannonfano    shannonfanoelias    tunstall    universal        expgolomb        fibonacci        gamma        levenshteindictionary type     byte pair encoding    deflate    lempelziv        lz  lz lz  lz        lzjb        lzma        lzo        lzrw        lzs        lzss        lzw        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or beliefs of conspiracy concerning a perceived threat towards oneself eg everyone is out to get me paranoia is distinct from phobias which also involve irrational fear but usually no blame making false accusations and the general distrust of others also frequently accompany paranoia for example an incident most people would view as an accident or coincidence a paranoid person might believe was intentionalcontents     history     use in modern psychiatry     symptoms     causes         social and environmental         physical     theories and mechanisms         abnormal reasoning         anomalous perceptual experiences         motivational factors     violence and paranoia     see also     notes     references     further readinghistorythe word paranoia comes from the greek paa paranoia madness and that from pa para beside by and  noos mind the term was used to describe a mental illness in which a delusional belief is the sole or most prominent feature in this definition the belief does not have to be persecutory to be classified as paranoid so any number of delusional beliefs can be classified as paranoiacitation needed for example a person who has the sole delusional belief that he is an important religious figure would be classified by kraepelin as having pure paranoiaaccording to michael phelan padraig wright and julian stern  paranoia and paraphrenia are debated entities that were detached from dementia praecox by kraepelin who explained paranoia as a continuous systematized delusion arising much later in life with no presence of either hallucinations or a deteriorating course paraphrenia as an identical syndrome to paranoia but with hallucinations even at the present time a delusion need not be suspicious or fearful to be classified as paranoid a person might be diagnosed as a paranoid schizophrenic without delusions of persecution simply because their delusions refer mainly to themselvesuse in modern psychiatryin the dsmivtr paranoia is diagnosed in the form of    paranoid personality disorder f    paranoid schizophrenia a subtype of schizophrenia f    the persecutory type of delusional disorder which is also called querulous paranoia when the focus is to remedy some injustice by legal action faccording to clinical psychologist p j mckenna as a noun paranoia denotes a disorder which has been argued in and out of existence and whose clinical features course boundaries and virtually every other aspect of which is controversial employed as an adjective paranoid has become attached to a diverse set of presentations from paranoid schizophrenia through paranoid depression to paranoid personalitynot to mention a motley collection of paranoid psychoses reactions and statesand this is to restrict discussion to functional disorders even when abbreviated down to the prefix para the term crops up causing trouble as the contentious but stubbornly persistent concept of paraphreniasymptomsa popular symptom of paranoia is the attribution bias these individuals typically have a biased perception of the world often exhibiting more hostile beliefs a paranoid person may view someone elses accidental behavior as though it is with intent or threateningan investigation of a nonclinical paranoid population found that feeling powerless and depressed isolating oneself and relinquishing activities are characteristics that could be associated with those exhibiting more frequent paranoia some scientists have created different subtypes for the various symptoms of paranoia including erotic persecutory litigious and exalted in addition sigmund freuds analerotic character triad is a salient symptom of the paranoid person some traits of this character can make group activities challenging which may lead to other social dilemmasdue to the suspicious and troublesome personality traits of paranoia it is unlikely that someone with paranoia will thrive in interpersonal relationships most commonly paranoid individuals tend to be of a single status according to some research there is a hierarchy for paranoia the least common types of paranoia at the very top of the hierarchy would be those involving more serious threats social anxiety is at the bottom of this hierarchy as the most frequently exhibited level of paranoiacausessocial and environmentalsocial circumstances appear to be highly influential on paranoid beliefs based on data collected by means of a mental health survey distributed to residents of juarez mexico and el paso texas paranoid beliefs seem to be associated with feelings of powerlessness and victimization enhanced by social situations potential causes of these effects included a sense of believing in external control and mistrust which can be strengthened by lower socioeconomic status those living in a lower socioeconomic status may feel less in control of their own lives in addition this study explains that females have the tendency to believe in external control at a higher rate than males potentially making females more susceptible to mistrust and the effects of socioeconomic status on paranoiaemanuel messinger reports that surveys have revealed that those exhibiting paranoia can evolve from parental relationships and distrustworthy environments these environments could include being very disciplinary stringent and unstable it was even noted that indulging and pampering thereby impressing the child that he is something special and warrants special privileges can be contributing backgrounds experiences likely to enhance or manifest the symptoms of paranoia include increased rates of disappointment stress and a hopeless state of minddiscrimination has also been reported as a potential predictor of paranoid delusions such reports that paranoia seemed to appear more in older patients that had experienced higher levels of discrimination throughout their lives in addition to this it has been noted that immigrants are quite susceptible to forms of psychosis this could be due to the aforementioned effects of discriminatory events and humiliationphysicala paranoid reaction may be caused from a decline in brain circulation as a result of high blood pressure or hardening of the arterial wallsbased on data obtained by the dutch nemisis project in  there was an association between impaired hearing and the onset of symptoms of psychosis which was based on a fiveyear follow up some older studies have actually declared that a state of paranoia can be produced in patients that were under a hypnotic state of deafness this idea however generated much skepticism during its timetheories and mechanismsabnormal reasoningmany researcherswho like to believe that individuals with paranoia have some sort of cognitive deficit or impairment in reasoning ability studies have shown that there may not be a direct relationship between the impairments and psychotic delusions but they rather impact other areas of an individuals life such as social circumstances which can be important factors for delusions other research has shown that cognitive abilities may be altered when threats were involved this appears to be a common theme among those exhibiting psychotic delusions an investigation involving one hundred delusional patients did actually reveal that these individuals may have a tendency to jump to conclusions rather than looking for other potential informationanomalous perceptual experiencesa very prominent example of this theory is the capgras delusion or syndrome named after the psychiatrist joseph capgras this involves an individual perceiving that a certain important person within their life has been taken over by an impersonator ellis and young  report that the capgras delusion may be a result of an impaired ability of recognition such as brain damage those suffering from the capgras syndrome tend to have more suspicious personalities and have unusual visualizations about the world and surrounding environmentshyperacute attention is said to be more common in those with paranoia by being able to attend to unfavorable emotions at a higher level it is also likely that because paranoid personalities focus on threatening events and believe that most intentions are against them they will be more inclined to recognize these behaviors more frequentlymotivational factorsthe attribution model has been well talked about regarding paranoid or delusional individuals the idea is that they like to assign issues to external events motivation behind this characteristic may involve the need for that person to develop a better selfimage and maintain selfconfidence there have been debates about whether or not paranoid individuals are more likely to have a low or high selfperception and results have been generated for both of these hypotheses researchers have made a distinction between positive selfesteem and negative selfesteem revealing that paranoid delusional individuals have more of a negative selfevaluationviolence and paranoiait has generally been agreed upon that individuals with paranoid delusions will have the tendency to take action based on their beliefs more research is needed on the particular types of actions that are pursued based on paranoid delusions some researchers have made attempts to distinguish the different variations of actions brought on as a result of delusions wessely et al  did just this by studying individuals with delusions of which more than half had reportedly taken action or behaved as a result of these delusions however the overall actions were not of a violent nature in most of the informants the authors note that other studies such as one by taylor  have shown that violent behaviors were more common in certain types of paranoid individuals mainly those with a history of being offensive such as prisonersother researchers have found associations between childhood abusive behaviors and the appearance of violent behaviors in psychotic individuals this could be a result of their inability to cope with aggression as well as other people especially when constantly attending to potential threats in their environment the attention to threat itself has been proposed as one of the major contributors of violent actions in paranoid people although there has been much deliberation about this as well other studies have shown that there may only be certain types of delusions that promote any violent behaviors persecutory delusions seem to be one of thesehaving resentful emotions towards others and the inability to be able to understand what other people are feeling seem to have an association with violence in paranoid individuals this was based on a study of paranoid schizophrenics one of the common mental disorders that exhibit paranoid symptoms theory of mind capabilities in relation to empathy the results of this study revealed specifically that although the violent patients were more successful at the higher level theory of mind tasks they were not as good at being able to interpret others feelingssee alsowikiquote has quotations related to paranoia    anxiety    borderline personality disorder    conspiracy theory    delusions of reference               distrust    fusion paranoia    ideas of reference    monomania    narcissistic personality disorder    paranoid personality disorder    paranoid social cognition    pronoia    querulant    religious paranoia    schizophrenia    whispers the voices of paranoianotes    world english dictionary collins english dictionary  complete  unabridged th edition  william collins sons  co ltd  informal sense intense fear or suspicion esp when unfounded    paa henry george liddell robert scott a greekenglish lexicon on perseus digital library    pa henry george liddell robert scott a greekenglish lexicon on perseus digital library     henry george liddell robert scott a greekenglish lexicon on perseus digital library    phelan wright and stern     american psychiatric association diagnostic and statistical manual of mental disorders    american psychiatric association diagnostic and statistical manual of mental disorders p    american psychiatric association diagnostic and statistical manual of mental disorders p    mckenna  p    bentall and taylor  p     freeman et al     deutsch and fishman p     deutsch and fishman  p     deutch and fishman  p    freeman et al  p    mirowski and ross     deutsch and fishman  p     deutsch and fishman  p     bentall and taylor  p     bentall and taylor  p    bentall and taylor     freeman et al  p     capgras and reboullachaux     ellis and young  p    bentall and taylor  p     barrowclough et al     bental and taylor  p     wessely et al     bentall and taylor p     bentall and taylor  p     bjorkly     abuakel and abushualeh references    american psychiatric association diagnostic and statistical manual of mental disorders dsmivtr fourth edition text revision      abuakel a abushualeh k  theory of mind in violent and nonviolent patients with paranoid schizophrenia schizophrenia research elsevier bv    dois inactive  pmid     barrowclough c tarrier n humphreys l ward j gregg l andrews b  selfesteem in schizophrenia relationships between selfevaluation family attitudes and symptomatology journal of abnormal psychology american psychological association    doix pmid     bentall rp taylor jl  psychological processes and paranoia implications for forensic behavioural science behavioral sciences and the law wiley interscience    doibsl pmid  retrieved april      bjorkly s  psychotic symptoms and violence toward others  a literature review of some preliminary findings part  delusions aggression and violent behavior elsevier ltd    dois    capgras j reboullachaux j  illusion des  sosies  dans un dlire systmatis chronique history of psychiatry sage publications    doix retrieved  april     deutsch alberted fishman helened  paranoia the encyclopedia of mental health vol iv the encyclopedia of mental health iv new york ny us franklin watts pp  doi retrieved april      ellis hd young aw  accounting for delusional misidentifications the british journal of psychiatry royal college of psychiatrists    doibjp pmid  retrieved  april     freeman d garety pa bebbington pe smith b rollinson r fowler d kuipers e ray k dunn g  psychological investigation of the structure of paranoia in a nonclinical population pdf the british journal of psychiatry the royal college of psychiatrists    doibjp retrieved march      freeman d garety pa fowler d kuipers e bebbington pe dunn g  why do people with delusions fail to choose more realistic explanations for their experiences an empirical investigation journal of consulting and clinical psychology american psychological association    doix pmid     mckenna pj  schizophrenia and related syndromes great britain psychology press isbn     mirowski j ross ce  paranoia and the structure of powerlessness   american sociological association pp  jstor     phelan michael wright padraig stern julian  core psychiatry philadelphia saunders isbn     wessely s buchanan a reed a cutting j everitt b garety p taylor pj  acting on delusions i prevalence the british journal of psychiatry the royal college of psychiatrists   doibjp pmid further reading    canneti elias  crowds and power translated from the german by carol stewart gollancz london     deutsch alberted fishman helened  paranoia the encyclopedia of mental health vol iv the encyclopedia of mental health iv new york ny us franklin watts pp  doi retrieved april      farrell john  paranoia and modernity cervantes to rousseau cornell university press    freeman d  garety p a  paranoia the psychology of persecutory delusions hove psychology press isbn x    igmade stephan trby et al eds  codes architecture paranoia and risk in times of terror birkhuser  isbn     kantor martin  understanding paranoia a guide for professionals families and sufferers westport praeger press isbn     munro a  delusional disorder cambridge cambridge university press isbn x    sant p  delusional disorder punjab panjab university chandigarh isbn x    sims a  symptoms in the mind an introduction to descriptive psychopathology rd edition edinburgh elsevier science ltd isbn     siegel ronald k  whispers the voices of paranoia new york crown isbn show    v    t    eemotions listshow    v    t    emental and behavioral disorders f authority control     ndl categories    abnormal psychology    psychosis    paranoia    metaphorsnavigation menu    create account    log in    article    talk    read    edit    view history    main page    contents    featured content    current events    random article    donate to wikipedia    wikipedia storeinteraction    help    about wikipedia    community portal    recent changes    contact pagetools    what links here    related changes    upload file    special pages    permanent link    page information    wikidata item    cite this pageprintexport    create a book    download as pdf    printable versionlanguages    alemannisch        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