A Newton learning approach for training a multilayer neural network is provided based on an efficient derivation of Hessian matrix of the network. Since the Newton's method converges almost quadratically, the conv...
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Results from an ongoing research project concerning detection and identification of signals in a relatively quiescent background are discussed. The signals to be identified are of varying duration, and the number of d...
A hybrid architecture for real-time monitoring and analysis of the VHF band is proposed. The design employs digital signalprocessing and neural network techniques for detection and classification, along with novel fu...
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An alternative view of neural-network-based phoneme recognition using multiresolution ideas and noncausal context is suggested. Some suggestions are made regarding target and error weight functions to improve performa...
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It is presented the electrical performance in Pspice for a VLSI Hamming neural net in CMOS 2-micron .technology, which features analog parallel processing and digital decoding, keeping the low circuit-interconnection ...
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The accurate classification of time sequences of vectors is a common goal in signalprocessing. Vector quantization (VQ) has commonly been used to help encode vectors for subsequent classification. The authors depart ...
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Using the properties of the nonlinear integral equations of the Hammerstein type, a new Lyapunov function for additive neuralnetworks is constructed. The function does not require monotonicity of the transfer functio...
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A VLSI architecture for real-time Markov random field optimization is presented. This architecture contains a simple and fast hardware module implementing the sigmoid function using look-up tables and piecewise linear...
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The relationship between snake active contours and Kohonen networks in the scope of object boundary detection is discussed. It is shown that these algorithms share many common features and that they are special cases ...
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A feedforwardneural network with sigmoidal activation functions is proposed to perform the wavelet decomposition of a discrete time signals. The proposed network is made of two parts, the main network and the auxilia...
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