This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing. The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields. Key Features: • Aimed at random signal processing with parametric signal processing-using appropriate segment size. • Covers speech, image, medical images, EEG and ECG signal processing. • Reviews optimal detection and estimation. • Discusses parametric modeling and signal processing in transform domain. • Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions

Covers advances in the field of computer techniques and algorithms in digital signal processing.

The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

Fundamentals of Signal Processing for Sound and Vibration Engineers is based on Joe Hammond’s many years of teaching experience at the Institute of Sound and Vibration Research, University of Southampton. Whilst the applications presented emphasise sound and vibration, the book focusses on the basic essentials of signal processing that ensures its appeal as a reference text to students and practitioners in all areas of mechanical, automotive, aerospace and civil engineering. Offers an excellent introduction to signal processing for students and professionals in the sound and vibration engineering field. Split into two parts, covering deterministic signals then random signals, and offering a clear explanation of their theory and application together with appropriate MATLAB examples. Provides an excellent study tool for those new to the field of signal processing. Integrates topics within continuous, discrete, deterministic and random signals to facilitate better understanding of the topic as a whole. Illustrated with MATLAB examples, some using ‘real’ measured data, as well as fifty MATLAB codes on an accompanying website.