1997 IEEE Workshop on Neural Networks for Signal Processing

• Record Nr.: UNINA9910872638603321
• Pubbl/distr/stampa: [Place of publication not identified], : IEEE, 1997
• Descrizione fisica: 1 online resource (680 pages)
• Disciplina: 006.32
• Soggetti: Neural networks (Computer science); Signal processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di contenuto: Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop -- Chaos, radar clutter, and neural networks -- Nonparametric regression modeling with topographic maps as a basis for lossy image compression -- Entropy manipulation of arbitrary nonlinear mappings -- Adaptive regularization of neural classifiers -- Remembering the past: the role of embedded memory in recurrent neural network architectures -- Low sensitivity time delay neural networks with cascade form structure -- Novel projection pursuit indices for feature extraction and classification: An inter-comparison in a remote sensing application -- Optimal feature extraction techniques to improve classification performance, with application to sonar signals -- On estimation of nonlinear black-box models: how to obtain a good initialization -- Interpretation of recurrent neural networks -- Extracting the relevant delays in time series modelling -- Combined learning and use for classification and regression models -- Reducing false alarm risk in transient signal classification -- Multiple and time-varying dynamic modelling capabilities of recurrent neural networks -- Induced specialization of context units for temporal pattern recognition and reproduction -- Uniform approximation and the complexity of neural networks -- Neural Networks for Medical Image Processing -- Mixture of discriminative learning experts of constant sensitivity for automated cytology screening -- Dynamics modelling in brain circulation -- A multiple-classifier architecture for ECG beat classification -- Applying ; neural networks to adjust insulin-pump doses -- MR brain image classification by multimodal perceptron tree neural network -- Texture analysis and artificial neural network for detection of clustered microcalcifications on mammograms -- Neural nets in boundary tracing tasks -- Neurocomputing applications in post-operative liver transplant monitoring -- Classification and compression of ICEGS using Gaussian mixture models -- Adaptive control in anaesthesia -- Wavelet characteristics of early vision -- Neural Networks and Gradient-Based Learning in OCR -- The gamma MLP-using multiple temporal resolutions for improved classification -- A deterministic annealing approach to discriminative hidden Markov model design -- An improved training algorithm for support vector machines -- Classification with linear networks using an online constrained LDA algorithm -- Combination of adaptive signal processing and neural classification using an extended backpropagation algorithm -- Wave propagation as a neural coupling mechanism: hardware for self-organizing feature maps and the representation of temporal sequences -- On-line adaptive algorithms in non-stationary environments using a modified conjugate gradient approach -- Segmentation and identification of drifting dynamical systems -- An improved scheme for the fuzzifier in fuzzy clustering -- Separable non-linear least-squares minimization-possible improvements for neural net fitting -- Training recurrent networks -- Combining discriminant-based classifiers using the minimum classification error discriminant -- Cross-entropy based pruning of the hierarchical mixtures of experts -- Blind separation of noisy mixtures -- One-unit contrast functions for independent component analysis: a statistical analysis -- Feature extraction approach to blind source separation -- Blind source separation of nonlinear mixing models -- Blind source separation: are information maximization and redundancy minimization different? -- Blind signal deconvolution by spatio-temporal decorrelation and demixing -- Multichannel blind separation and deconvolution of sources with arbitrary distributions -- Recurrent canonical piecewise linear network: theory and application -- Blind source separation and deconvolution by dynamic component analysis -- Neural dual extended Kalman filtering: applications in speech enhancement and monaural blind signal separation -- Bayesian Ying-Yang learning based ICA models -- A neural network approach to blind source separation -- A unifying criterion for blind source separation and decorrelation: simultaneous diagonalization of correlation matrices -- Neural Networks for Intelligent Multimedia Processing -- Nonlinear prediction of chaotic time series using support vector machines -- A DCT-based adaptive metric learning model using asymptotic local information measure -- Sub-word speaker verification using data fusion methods -- A chaotic annealing neural network and its application to direction estimation of spatial signal sources -- A neural network equalizer with the fuzzy decision learning rule -- Application of the block recursive least squares algorithm to adaptive neural beamforming -- Nonlinear committee pattern classification -- Unsupervised speaker classification using self-organizing maps (SOM) -- A self-scaling neural hardware structure that reduces the effect of some implementation errors -- Application of neural networks to the problem of forecasting the flow of the River Nile -- Robustness of a chaotic modal neural network applied to audio-visual speech recognition -- Applying neural networks and other AI techniques to fault detection in satellite communication systems -- Multi-linguistic handwritten character recognition by Bayesian decision-based neural networks -- Neural networks for engine fault diagnostics -- Locally recurrent networks ; with multiple time-scales -- Medical image analysis by probabilistic modular neural networks -- Author index.
• Sommario/riassunto: This workshop is designed to serve as a regular forum universities and industry who are interested in interdisciplinary research on neutral networks for signal processing applications.