Network models and associated applications

Network models and associated applicatio

📁 Network models and associated applications (Mathematical programming study, No. 15)

✍ D. Klingman, J. M. Mulvey 📂 Library 📅 1981 🌐 English

Neural Networks: Computational Models an

📁 Neural Networks: Computational Models and Applications

✍ Huajin Tang, Kay Chen Tan, Zhang Yi 📂 Library 📅 2007 🏛 Springer 🌐 English

Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications

Neural Networks: Computational Models an

📁 Neural Networks: Computational Models and Applications

✍ Dr. Huajin Tang, Prof. Kay Chen Tan, Prof. Zhang Yi (auth.) 📂 Library 📅 2007 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

<p><P>Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and th

Adaptive networks: theory, models and ap

📁 Adaptive networks: theory, models and applications

✍ Thilo Gross, Hiroki Sayama (auth.), Thilo Gross, Hiroki Sayama (eds.) 📂 Library 📅 2009 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

Neural Networks Computational Models an

📁 Neural Networks Computational Models and Applications

✍ Huajin Tang, Kay Chen Tan, Zhang Yi 📂 Library 📅 2007 🏛 Springer 🌐 English

Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications

Bayesian Network Technologies: Applicati

📁 Bayesian Network Technologies: Applications and Graphical Models

✍ Ankush Mittal, Ankush Mittal; Ashraf Kassim 📂 Library 📅 2007 🏛 IGI Publishing 🌐 English

Bayesian networks are now being used in a variety of artificial intelligence applications. These networks are high-level representations of probability distributions over a set of variables that are used for building a model of the problem domain. Bayesian Network Technologies: Applications and G