In recent decades, the study of signal processing has become increasingly complex, with new techniques and applications constantly being developed for the processing, transformation, and interpretation of signals. This book provides a comprehensive introduction to the traditional and modern methods used in signal processing. It is designed to...

Complex interacting networks are observed in systems from such diverse areas as physics, biology, economics, ecology, and computer science. For example, economic or social interactions often organize themselves in complex network structures. Similar phenomena are observed in traffic flow and in communication networks as the internet. In...

The 115 revised...

This book provides a general introduction to Bayesian networks,...

Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear dynamic-observation system, under the regular conditions such as perfect data information; complete noise statistics; exact linear modelling; ideal will-conditioned matrices in computation and strictly...

The support vector machine (SVM) is a supervised learning method that generates input-output mapping functions from a set of labeled training data. The mapping function can be either a classification function, i.e., the category of the input data, or a regression function. For classification, nonlinear kernel functions are often used to...