High Dimensional Neurocomputing Growth, Appraisal and Applications / by Bipin Kumar Tripathi.
By: Tripathi, Bipin Kumar., autor.
Material type:
E-bookSeries: (Studies in Computational Intelligence,, 1860-949X ;; 571); (Engineering (Springer-11647)).Publisher: New Delhi : Springer International Publishing, 2015Description: 1 recurso en línea (XIX, 165 páginas 49 ilustraciones).ISBN: 9788132220749.Subject: Redes neuronales artificiales
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.87 T757 2015 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.12112212 |
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| QA76.87 P357 2017 EB Granular neural networks, pattern recognition and bioinformatics | QA76.87 P373 2015 EB Paraconsistent Intelligent-Based Systems New Trends in the Applications of Paraconsistency | QA76.87 R543 2015 EB Advanced Models of Neural Networks : Nonlinear Dynamics and Stochasticity in Biological Neurons | QA76.87 T757 2015 EB High Dimensional Neurocomputing Growth, Appraisal and Applications | QA76.87 W36 2016 EB Qualitative Analysis and Control of Complex Neural Networks with Delays | QA76.87 W364 2018 EB Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms | QA76 .87 Y333 2015 EB An Introduction to Neural Network Methods for Differential Equations |
Neuro-Computing with High Dimensional Parameters -- Neuro-Computing in Complex Domain -- Higher Order Computational Model of Novel Neurons -- Neuro-Computing in Space -- High Dimensional Mapping -- Machine Recognition for Biometric Application in Complex Domain.
The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligence.
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