Artificial Neural Networks

Abstract Artificial neural networks are useful tools that have been applied successfully in a broad range of signal‐processing problems. From a signal‐processing perspective, their ability to adapt continuously to new data allows them to track changes in a signal over time, and their ability to learn from arbitrary, noisy data permits them to solve problems that cannot be handled adequately with some of the conventional statistical techniques. This chapter presents the fundamental principles of neural network modeling and illustrates some of the most commonly used neural network architectures for practical problem solving.

# Neural Networks and Applications # Computer Science # Machine Learning and ELM # Advanced Adaptive Filtering Techniques # Engineering

Ajith Abraham (2005). "Artificial Neural Networks". Wiley eBooks. https://doi.org/10.1002/0471497398.mm421