To provide a mechanism that could perform this function for a limited range of stimuli is to provide a sensory basis for memory, for the construction of expectations (e.g., about objects or other sensory events), and for the construction and management of complex relationships (see Attn eave, 1954; Lippmann, 1954). In the context of memory, the sensory system can also be thought of as an information processor and is often referred to as an information cache. A cache is an arrangement to store or preserve information, to retrieve it from memory, and to pass it on to other processors (e.g., a processing unit or a memory device). The storage of information is the most obvious functional element of the sensory system. What makes a cache important for memory? A cache is a system for storing or recalling information in such a way that the information will be easily available to the processor in the future (see Lippmann, 1954). However, information stored in a cache cannot be stored or retrieved as quickly or as reliably as a full copy of the information, since changes made to the information by the processor after retrieval are not immediately reflected in the information. In contrast, full copies of information stored in caches, especially in long time intervals, are often stored and retrieved more quickly and reliably than are full copies stored in temporary locations in the synaptic networks. In his 1959 review of memory theory, Wachsmuth (1959: 19.2) notes that, “If all processing systems were designed to record indefinitely in an artificial memory, our data would last forever We do not live like that. We must use short time intervals to store information.” Information storage and revivability rely on the concept of independence in a number of related fields. These include logic, probability, and computation.
Logic
Logic theory was devised by David Hilbert in the early years of his career. Hilbert was inspired by the work of the German mathematician Carl Friedrich Gauss. Gauss, in 1785, had shown that it is possible for a system of a finite complexity to exhibit a complete set of “laws of nature”, in which all the laws have the form “X always causes Y”. The logical consequence of this is that by making some assumptions, one obtains a complete system. For example, one can deduce from the existence of the law that there exist a number (say, 10) such that for all values of the value 10, a number always exists.
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Information Theory Recommended readings: Simon Hay kin: Neural Networks: a comprehensive foundation, Prentice Hall, 1999, chapter Information Theoretic Models. HPV risen, J. Karen, E. OMA: Independent
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