E. S. Gopi – författare

This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques.

This book provides in-depth exposure to emerging technologies and recent advancements in RF, Microwave, and Millimetre Wave Technologies. The book covers the basic concepts along with the recent advancements in designing and developing antennas and circuits for the latest technologies. The concepts of mode compression, Full Duplex communication, massive MIMO, frequency selective surfaces, reflectarrays, and metasurfaces have been discussed in detail. Various types of antennas, such as electrically small antennas, textile antennas, dielectric resonator antennas, etc., to be used for the latest wireless devices, RFID applications are also thoroughly explored. The concept of machine learning to develop data-driven models for antenna design is also discussed briefly to provide readers with an introduction to the ML algorithms. The readers will be able to understand the theoretical concepts and practical design aspects of various antennas, high-frequency circuits, and device modeling. The target audience includes but is not limited to undergraduates, post-graduates, research scholars, academicians, scientists, and professionals who are interested in getting the latest knowledge in the field of RF, Microwave, and Millimetre Wave Technologies.

Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

Mathematical summary for Digital Signal Processing Applications with Matlab consists of Mathematics which is not usually dealt in the DSP core subject, but used in DSP applications. Matlab programs with illustrations are given for the selective topics such as generation of Multivariate Gaussian distributed sample outcomes, Bacterial foraging algorithm, Newton’s iteration, Steepest descent algorithm, etc. are given exclusively in the separate chapter. Also Mathematical summary for Digital Signal Processing Applications with Matlab is written in such a way that it is suitable for Non-Mathematical readers and is very much suitable for the beginners who are doing research in Digital Signal Processing.