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By Professor Dr. Berndt Müller, Dr. Joachim Reinhardt, Michael T. Strickland (auth.)
Neural Networks The innovations of neural-network versions and methods of parallel allotted processing are comprehensively awarded in a three-step method: - After a short evaluation of the neural constitution of the mind and the background of neural-network modeling, the reader is brought to associative reminiscence, preceptrons, feature-sensitive networks, studying concepts, and useful purposes. - the second one half covers extra complex topics reminiscent of the statistical physics of spin glasses, the mean-field idea of the Hopfield version, and the "space of interactions" method of the garage potential of neural networks. - within the self-contained ultimate half, seven courses that supply useful demonstrations of neural-network types and their studying innovations are mentioned. The software program is integrated on a three 1/2-inch MS-DOS diskette. The resource code will be transformed utilizing Borland's TURBO-C 2.0 compiler, the Microsoft C compiler (5.0), or appropriate compilers.
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In other words the networks suddenly jumps from almost perfect memory into a state of complete confusion. 3 The understanding of this surprising result by means of methods developed in the statistical theory of spin-glass systems, to be discussed in Part II, has kindled the interest of theoretical physicists in neural networks and in brain models in general. 5 o. 05 or 3 Fig. 5. 138. A second, much more restrictive approach can be taken to define the memory capacity. One may require error-free recall, which means that the stored patterns have to be attractors of the network, without there being any errors introduced by interference among them.
Associative Memory when the number of stored patterns is much smaller than the total number of neurons in the network, the additional term will most likely not affect the sign of the complete expression h~v), which alone determines the reaction of the ith neuron. e. the network configuration will converge to the desired pattern within a single global update. 15) becomes of order one, and the patterns can no longer be recalled reliably. e. 14. An explicit expression is obtained by means of the Fourier transform p(k, 1) == j dxp(x, 1) exp(ikx) = ~ [exp(ik) + exp( -ik)] = cos(k) .
138 and ends, as we just have found, at T = 1 for a = o. At the phase boundary m falls discontinuously to zero, except for T = 0, where the change is continuous, but not differentiable. 4 This behavior is illustrated in Fig. 7.