Title
Fundamentals Of Artificial Neural Networks,New
Delivery time: 8-12 business days (International)
As Book Review Editor Of The Ieee Transactions On Neural Networks, Mohamad Hassoun Has Had The Opportunity To Assess The Multitude Of Books On Artificial Neural Networks That Have Appeared In Recent Years. Now, In Fundamentals Of Artificial Neural Networks, He Provides The First Systematic Account Of Artificial Neural Network Paradigms By Identifying Clearly The Fundamental Concepts And Major Methodologies Underlying Most Of The Current Theory And Practice Employed By Neural Network Researchers.Such A Systematic And Unified Treatment, Although Sadly Lacking In Most Recent Texts On Neural Networks, Makes The Subject More Accessible To Students And Practitioners. Here, Important Results Are Integrated In Order To More Fully Explain A Wide Range Of Existing Empirical Observations And Commonly Used Heuristics. There Are Numerous Illustrative Examples, Over 200 Endofchapter Analytical And Computerbased Problems That Will Aid In The Development Of Neural Network Analysis And Design Skills, And A Bibliography Of Nearly 700 References.Proceeding In A Clear And Logical Fashion, The First Two Chapters Present The Basic Building Blocks And Concepts Of Artificial Neural Networks And Analyze The Computational Capabilities Of The Basic Network Architectures Involved. Supervised, Reinforcement, And Unsupervised Learning Rules In Simple Nets Are Brought Together In A Common Framework In Chapter Three. The Convergence And Solution Properties Of These Learning Rules Are Then Treated Mathematically In Chapter Four, Using The 'Average Learning Equation' Analysis Approach. This Organization Of Material Makes It Natural To Switch Into Learning Multilayer Nets Using Backprop And Its Variants, Described In Chapter Five. Chapter Six Covers Most Of The Major Neural Network Paradigms, While Associative Memories And Energy Minimizing Nets Are Given Detailed Coverage In The Next Chapter. The Final Chapter Takes Up Boltzmann Machines And Boltzmann Learning Along With Other Global Search/Optimization Algorithms Such As Stochastic Gradient Search, Simulated Annealing, And Genetic Algorithms.
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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
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We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.
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