

Likelihood function of cji with respect to x Li(vi, r*i, Mi) Hyperellipsoidal shell prototype of the fuzzyįactor of the sampling rate change (either decimation orįeedforward weight matrix between field F x and field F yįeedback weight matrix between field F y and field F x

Hyperspherical shell prototype of the fuzzy Language or log-likelihood function in ICA KuUback divergence between the pdfs / and g Inverse covariance matrix of the zth receptive field Prototypes L described by set of radii R and centers V J ( P, V, i ?, M ) Criterion function for partition P and hyperellipsoidal Inadequacy between a fuzzy class Ai and its prototype L^Ĭriterion function (inadequacy) for partition P andĬriterion function for partition P and representation LĬriterion function for partition P and hypersphere Hyi,-,yn i) mutual information between m random variables yi Probability that a given difference ys occurs (Differential) entropy of stochastic signal y Output function of the ith neuron for the current activityįilter coefficients in the synthesis part Mahalanobis distance of the ith receptive fieldĭissimilarity between a data point Xj andĮrror function due to the pth feature vectorĮvaluation associated with the ith stringĪverage evaluation of all strings in the population Wavelet coefficient at scale m and translation n Scaling coefficient at scale m and translation n Vector of lateral connections of the ith neuron Single-photon-emission-computer-tomographyĬonnection between the ith and the j t h neuron of the same Perfect reconstruction quadrature mirror filter Adaptive principal components analysis using lateralįuzzy algorithm for learning vector quantization
