{"product_id":"information-theoretic-aspects-of-neural-networks-hardback","title":"Information-Theoretic Aspects of Neural Networks - Hardback","description":"\u003cp\u003eInformation theoretics vis-a-vis neural networks generally embodies parametric entities and conceptual bases pertinent to memory considerations and information storage, information-theoretic based cost-functions, and neurocybernetics and self-organization. Existing studies only sparsely cover the entropy and\/or cybernetic aspects of neural information.\u003cbr\u003eInformation-Theoretic Aspects of Neural Networks cohesively explores this burgeoning discipline, covering topics such as:\u003c\/p\u003e\u003cli\u003eShannon information and information dynamics\u003cbr\u003e \u003c\/li\u003e\u003cli\u003eneural complexity as an information processing system\u003cbr\u003e \u003c\/li\u003e\u003cli\u003ememory and information storage in the interconnected neural web\u003cbr\u003e \u003c\/li\u003e\u003cli\u003eextremum (maximum and minimum) information entropy\u003cbr\u003e \u003c\/li\u003e\u003cli\u003eneural network training\u003cbr\u003e \u003c\/li\u003e\u003cli\u003enon-conventional, statistical distance-measures for neural network optimizations\u003cbr\u003e \u003c\/li\u003e\u003cli\u003esymmetric and asymmetric characteristics of information-theoretic error-metrics\u003cbr\u003e \u003c\/li\u003e\u003cli\u003ealgorithmic complexity based representation of neural information-theoretic parameters\u003cbr\u003e \u003c\/li\u003e\u003cli\u003egenetic algorithms versus neural information\u003cbr\u003e \u003c\/li\u003e\u003cli\u003edynamics of neurocybernetics viewed in the information-theoretic plane\u003cbr\u003e \u003c\/li\u003e\u003cli\u003enonlinear, information-theoretic transfer function of the neural cellular units\u003cbr\u003e \u003c\/li\u003e\u003cli\u003estatistical mechanics, neural networks, and information theory\u003cbr\u003e \u003c\/li\u003e\u003cli\u003esemiotic framework of neural information processing and neural information flow\u003cbr\u003e \u003c\/li\u003e\u003cli\u003efuzzy information and neural networks\u003cbr\u003e \u003c\/li\u003e\u003cli\u003eneural dynamics conceived through fuzzy information parameters\u003cbr\u003e \u003c\/li\u003e\u003cli\u003eneural information flow dynamics\u003cbr\u003e \u003c\/li\u003e\u003cli\u003einformatics of neural stochastic resonance\u003cbr\u003eInformation-Theoretic Aspects of Neural Networks acts as an exceptional resource for engineers, scientists, and computer scientists working in the field of artificial neural networks as well as biologists applying the concepts of communication theory and protocols to the functioning of the brain. The information in this book explores new avenues in the field and creates a common platform for analyzing the neural complex as well as artificial neural networks.\u003c\/li\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Default Title","offer_id":45547378999534,"sku":"9780849331985","price":294.4,"currency_code":"AUD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0630\/9612\/7726\/files\/9780849331985.jpg?v=1720247741","url":"https:\/\/bookland.com.au\/products\/information-theoretic-aspects-of-neural-networks-hardback","provider":"Book Land AU","version":"1.0","type":"link"}