ΠΡΡ ΠΎΠ΄Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ Π½Π΅ΠΈΠ·Π²Π΅ΡΡΠ½Ρ<br/>The Neural Network Toolbox is written so that if you read Chapter 2, Chapter 3 and Chapter 4 you can proceed to a later chapter, read it and use its functions without difficulty. To make this possible, Chapter 2 presents the fundamentals of the neuron model, the archit
Introduction to Neural Networks Using MATLAB 6.0
β Scribed by S. N. Sivanandam; S. Sumathi; S. N. Deepa
- Publisher
- Tata McGraw-Hill Education
- Year
- 2006
- Tongue
- English
- Leaves
- 548
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Written for undergraduate students in computer science, this book provides a comprehensive overview of the field of neural networks. The book presents readers with the application of neural networks to areas like bioinformatics, robotics, communication, image processing, and healthcare. Topics covered include fundamental models of artificial neural networks, perception networks, and adaptive resonance theory.
π SIMILAR VOLUMES
Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gra
Please note this is a Short Discount publication. Neural network technology has been a curiosity since the early days of computing. Research in the area went into a near dormant state for a number of years, but recently there has been a new increased interest in the subject. This has been due to a n
An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in te