Principles Of Neurocomputing For Science And Engineering
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Principles of Neurocomputing for Science and Engineering
This exciting new text covers artificial neural networks, but more specifically, neurocomputing. Neurocomputing is concerned with processing information, which involves a learning process within an artificial neural network architecture. This neural architecture responds to inputs according to a defined learning rule and then the trained network can be used to perform certain tasks depending on the application. Neurocomputing can play an important role in solving certain problems such as pattern recognition, optimization, event classification, control and identification of nonlinear systems, and statistical analysis. "Principles of Neurocomputing for Science and Engineering," unlike other neural networks texts, is written specifically for scientists and engineers who want to apply neural networks to solve complex problems. For each neurocomputing concept, a solid mathematical foundation is presented along with illustrative examples to accompany that particular architecture and associated training algorithm. The book is primarily intended for graduate-level neural networks courses, but in some instances may be used at the undergraduate level. The book includes many detailed examples and an extensive set of end-of-chapter problems.
Proceedings of the Fifth International Conference on Emerging Trends in Mathematical Sciences & Computing (IEMSC-24)
Author: Biswadip Basu Mallik
language: en
Publisher: Springer Nature
Release Date: 2024-10-31
The Proceedings of the Fifth International Conference on Emerging Trends in Mathematical Sciences & Computing (IEMSC-24) contains papers that present the current scientific as well as technological innovations by leading academicians, eminent researchers, and experts throughout the globe in the twin domain of Mathematical Sciences as well as Computing. The papers focus on the recent advances in the field of Theoretical Computer Science as well as its blending with Mathematical techniques. The book aims to disseminate new technical ideas and features that can be incorporated in day-to-day life for the benefit of the society. The research papers exhibit scientific advancements in diversified spectrum that includes Differential as well as Integral Equations with applications, Computational Fluid Dynamics, Nanofluids, Network Theory & Optimization, Control Theory, Machine Learning & Artificial Intelligence, Big Data Analytics, IoT, Cryptography, Fuzzy Automata, Statistics, and many more. The proceedings primarily focus on the amalgamation of mathematical methods with computing. The potential readers will get access to diverse ideas and innovations in the field of computing together with its growing interactions in various fields of mathematics. This book serves as a valuable reference resource for researchers in academia and industry.
Handbook of Research on Advanced Computational Techniques for Simulation-Based Engineering
Recent developments in information processing systems have driven the advancement of computational methods in the engineering realm. New models and simulations enable better solutions for problem-solving and overall process improvement. The Handbook of Research on Advanced Computational Techniques for Simulation-Based Engineering is an authoritative reference work representing the latest scholarly research on the application of computational models to improve the quality of engineering design. Featuring extensive coverage on a range of topics from various engineering disciplines, including, but not limited to, soft computing methods, comparative studies, and hybrid approaches, this book is a comprehensive reference source for students, professional engineers, and researchers interested in the application of computational methods for engineering design.