eTEXT
Neural Networks and Statistical Learning
By: Ke-Lin Du, M. N. S. Swamy
eText | 12 September 2019 | Edition Number 2
At a Glance
New Edition
eText
$159.25
Instant online reading in your Booktopia eTextbook Library *
Read online on
Not downloadable to your eReader or an app
Why choose an eTextbook?
Instant Access *
Purchase and read your book immediately
Read Aloud
Listen and follow along as Bookshelf reads to you
Study Tools
Built-in study tools like highlights and more
* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.
This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing.
Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include:
• multilayer perceptron;
• the Hopfield network;
• associative memory models;• clustering models and algorithms;
• t he radial basis function network;
• recurrent neural networks;
• nonnegative matrix factorization;
• independent component analysis;
•probabilistic and Bayesian networks; and
• fuzzy sets and logic.
Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.
Read online on
ISBN: 9781447174523
ISBN-10: 1447174526
Published: 12th September 2019
Format: ePUB
Language: English
Publisher: Springer Nature
Edition Number: 2
You Can Find This eBook In
Other Editions and Formats
This product is categorised by
- Non-FictionMathematicsApplied MathematicsMathematical Modelling
- Non-FictionEngineering & TechnologyTechnology in GeneralEngineering in General
- Non-FictionComputing & I.T.Computer ScienceArtificial IntelligenceComputer Vision
- Non-FictionEngineering & TechnologyElectronics & Communications EngineeringElectronics Engineering
- Non-FictionComputing & I.T.Computer ScienceArtificial IntelligencePattern Recognition
- Non-FictionComputing & I.T.Computer ScienceImage Processing