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Fusion Adaptive Resonance Theory
Fusion adaptive resonance theory (fusion ART) is a generalization of self-organizing Neural network, neural networks known as the original Adaptive resonance theory, Adaptive Resonance TheoryCarpenter, G.A. & Grossberg, S. (2003)Adaptive Resonance Theory, In Michael A. Arbib (Ed.), The Handbook of Brain Theory and Neural Networks, Second Edition (pp. 87-90). Cambridge, MA: MIT Press models for learning recognition categories across multiple pattern channels. There is a separate stream of work on fusion ARTMAP,Y.R. Asfour, G.A. Carpenter, S. Grossberg, and G.W. Lesher. (1993) Fusion ARTMAP: an adaptive fuzzy network for multi-channel classification. In Proceedings of the Third International Conference on Industrial Fuzzy Control and Intelligent Systems (IFIS).R.F. Harrison and J.M. Borges. (1995) Fusion ARTMAP: Clarification, Implementation and Developments. Research Report No. 589, Department of Automatic Control and Systems Engineering, The University of Sheffield. that extends fuz ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recall (memory)
Recall in memory refers to the mental process of retrieval of information from the past. Along with encoding and storage, it is one of the three core processes of memory. There are three main types of recall: free recall, cued recall and serial recall. Psychologists test these forms of recall as a way to study the memory processes of humansrecall. (2010). In Encyclopædia Britannica. Retrieved March 04, 2010, from Encyclopædia Britannica Online: http://www.britannica.com/EBchecked/topic/493353/recal/ref> and animals. Two main theories of the process of recall are the two-stage theory and the theory of Encoding specificity principle, encoding specificity. Theories Two-stage theory The ''two-stage theory'' states that the process of recall begins with a search and retrieval process, and then a decision or recognition process where the correct information is chosen from what has been retrieved. In this theory, recognition only involves the latter of these two stages, or processes, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Q-value (statistics)
In statistical hypothesis testing, specifically Multiple comparisons problem, multiple hypothesis testing, the ''q''-value in the Storey-Tibshirani procedure provides a means to control the False discovery rate#Related error rates, positive false discovery rate (pFDR). Just as the P-value, ''p''-value gives the expected false positive rate obtained by rejecting the null hypothesis for any result with an equal or smaller ''p''-value, the ''q''-value gives the expected pFDR obtained by rejecting the null hypothesis for any result with an equal or smaller ''q''-value. History In statistics, testing multiple hypotheses simultaneously using methods appropriate for testing single hypotheses tends to yield many false positives: the so-called multiple comparisons problem. For example, assume that one were to test 1,000 null hypotheses, all of which are true, and (as is conventional in single hypothesis testing) to reject null hypotheses with a significance level of 0.05; due to random ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autonomy
In developmental psychology and moral, political, and bioethical philosophy, autonomy, from , ''autonomos'', from αὐτο- ''auto-'' "self" and νόμος ''nomos'', "law", hence when combined understood to mean "one who gives oneself one's own law" is the capacity to make an informed, uncoerced decision. Autonomous organizations or institutions are independent or self-governing. Autonomy can also be defined from a human resources perspective, where it denotes a (relatively high) level of discretion granted to an employee in his or her work. In such cases, autonomy is known to generally increase job satisfaction. Self-actualized individuals are thought to operate autonomously of external expectations. In a medical context, respect for a patient's personal autonomy is considered one of many fundamental ethical principles in medicine. Sociology In the sociology of knowledge, a controversy over the boundaries of autonomy inhibited analysis of any concept beyond relative auto ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
If Clause
Conditional sentences are natural language sentences that express that one thing is contingent on something else, e.g. "If it rains, the picnic will be cancelled." They are so called because the impact of the main clause of the sentence is ''conditional'' on the dependent clause. A full conditional thus contains two clauses: a dependent clause called the ''antecedent'' (or ''protasis'' or ''if-clause''), which expresses the condition, and a main clause called the ''consequent'' (or ''apodosis'' or ''then-clause'') expressing the result. Languages use a variety of grammatical forms and constructions in conditional sentences. The forms of verbs used in the antecedent and consequent are often subject to particular rules as regards their tense, aspect, and mood. Many languages have a specialized type of verb form called the conditional mood – broadly equivalent in meaning to the English "would (do something)" – for use in some types of conditional sentences. Types of conditiona ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Consequent
A consequent is the second half of a hypothetical proposition. In the standard form of such a proposition, it is the part that follows "then". In an implication, if ''P'' implies ''Q'', then ''P'' is called the antecedent and ''Q'' is called the consequent. In some contexts, the consequent is called the ''apodosis''.See Conditional sentence. Examples: * If P, then Q. Q is the consequent of this hypothetical proposition. * If X is a mammal, then X is an animal. Here, "X is an animal" is the consequent. * If computers can think, then they are alive. "They are alive" is the consequent. The consequent in a hypothetical proposition is not necessarily a consequence of the antecedent. * If monkeys are purple, then fish speak Klingon. "Fish speak Klingon" is the consequent here, but intuitively is not a consequence of (nor does it have anything to do with) the claim made in the antecedent that "monkeys are purple. See also * Antecedent (logic) * Conjecture * Necessity and su ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Support Vector Machine
In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Developed at AT&T Bell Laboratories by Vladimir Vapnik with colleagues (Boser et al., 1992, Guyon et al., 1993, Cortes and Vapnik, 1995, Vapnik et al., 1997) SVMs are one of the most robust prediction methods, being based on statistical learning frameworks or VC theory proposed by Vapnik (1982, 1995) and Chervonenkis (1974). Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples to one category or the other, making it a non- probabilistic binary linear classifier (although methods such as Platt scaling exist to use SVM in a probabilistic classification setting). SVM maps training examples to points in space so as to maximise the width of the gap between the two categories. New ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
K-nearest Neighbors Algorithm
In statistics, the ''k''-nearest neighbors algorithm (''k''-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, and later expanded by Thomas Cover. It is used for classification and regression. In both cases, the input consists of the ''k'' closest training examples in a data set. The output depends on whether ''k''-NN is used for classification or regression: :* In ''k-NN classification'', the output is a class membership. An object is classified by a plurality vote of its neighbors, with the object being assigned to the class most common among its ''k'' nearest neighbors (''k'' is a positive integer, typically small). If ''k'' = 1, then the object is simply assigned to the class of that single nearest neighbor. :* In ''k-NN regression'', the output is the property value for the object. This value is the average of the values of ''k'' nearest neighbors. If ''k'' = 1, then the output is simply assigned to the v ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Synchronizing
Synchronization is the coordination of events to operate a system in unison. For example, the conductor of an orchestra keeps the orchestra synchronized or ''in time''. Systems that operate with all parts in synchrony are said to be synchronous or ''in sync''—and those that are not are ''asynchronous''. Today, time synchronization can occur between systems around the world through satellite navigation signals and other time and frequency transfer techniques. Navigation and railways Time-keeping and synchronization of clocks is a critical problem in long-distance ocean navigation. Before radio navigation and satellite-based navigation, navigators required accurate time in conjunction with astronomical observations to determine how far east or west their vessel traveled. The invention of an accurate marine chronometer revolutionized marine navigation. By the end of the 19th century, important ports provided time signals in the form of a signal gun, flag, or dropping time ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Choice Function
A choice function (selector, selection) is a mathematical function ''f'' that is defined on some collection ''X'' of nonempty sets and assigns some element of each set ''S'' in that collection to ''S'' by ''f''(''S''); ''f''(''S'') maps ''S'' to some element of ''S''. In other words, ''f'' is a choice function for ''X'' if and only if it belongs to the direct product of ''X''. An example Let ''X'' = . Then the function that assigns 7 to the set , 9 to , and 2 to is a choice function on ''X''. History and importance Ernst Zermelo (1904) introduced choice functions as well as the axiom of choice (AC) and proved the well-ordering theorem, which states that every set can be well-ordered. AC states that every set of nonempty sets has a choice function. A weaker form of AC, the axiom of countable choice (ACω) states that every countable set of nonempty sets has a choice function. However, in the absence of either AC or ACω, some sets can still be shown to have a ch ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vigilance (psychology)
In modern psychology, vigilance, also termed sustained concentration, is defined as the ability to maintain concentrated attention over prolonged periods of time. During this time, the person attempts to detect the appearance of a particular target stimulus. The individual watches for a signal stimulus that may occur at an unknown time. The study of vigilance has expanded since the 1940s mainly due to the increased interaction of people with machines for applications involving monitoring and detection of rare events and weak signals. Such applications include air traffic control, inspection and quality control, automated navigation, military and border surveillance, and lifeguarding. Origins of research The systematic study of vigilance was initiated by Norman Mackworth during World War II. Mackworth authored "The breakdown of vigilance during prolonged visual search" in 1948 and this paper is the seminal publication on vigilance. Mackworth's 1948 study investigated the tendency o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vector Space
In mathematics and physics, a vector space (also called a linear space) is a set whose elements, often called ''vectors'', may be added together and multiplied ("scaled") by numbers called '' scalars''. Scalars are often real numbers, but can be complex numbers or, more generally, elements of any field. The operations of vector addition and scalar multiplication must satisfy certain requirements, called ''vector axioms''. The terms real vector space and complex vector space are often used to specify the nature of the scalars: real coordinate space or complex coordinate space. Vector spaces generalize Euclidean vectors, which allow modeling of physical quantities, such as forces and velocity, that have not only a magnitude, but also a direction. The concept of vector spaces is fundamental for linear algebra, together with the concept of matrix, which allows computing in vector spaces. This provides a concise and synthetic way for manipulating and studying systems of linear eq ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
