Digital Signal Processing Fundamentals Applications And Deep Learning Pdf
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Digital Signal Processing
Digital Signal Processing: Fundamentals, Applications, and Deep Learning, Fourth Edition introduces students to the fundamental principles of digital signal processing (DSP) while also providing a working knowledge that they take with them into their engineering careers. Many instructive, worked examples are used to illustrate the material, and the use of mathematics is minimized for an easier grasp of concepts. As such, this title is also useful as a reference for non-engineering students and practicing engineers.This book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include DSP for artificial intelligence, adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as pulse-code modulation, μ-law, adaptive differential pulse-code modulation, multi-rate DSP, oversampling analog-to-digital conversion, sub-band coding, wavelet transform, and neural networks. - Covers DSP principles with various examples of real-world DSP applications on noise cancellation, communications, control applications, and artificial intelligence - Includes application examples using DSP techniques for deep learning neural networks to solve real-world problems - Provides a new chapter to cover principles of artificial neural networks and convolution neural networks with back-propagation algorithms - Provides hands-on practice, with MATLAB code for worked examples and C programs for real-time DSP for students at https://www.elsevier.com/books-and-journals/book-companion/9780443273353 - Offers teaching support, including an image bank, full solutions manual, and MATLAB projects for qualified instructors, available for request at https://educate.elsevier.com/9780443273353
Digital Twin – Fundamental Concepts to Applications in Advanced Manufacturing
This book provides readers with a guide to the use of Digital Twin in manufacturing. It presents a collection of fundamental ideas about sensor electronics and data acquisition, signal and image processing techniques, seamless data communications, artificial intelligence and machine learning for decision making, and explains their necessity for the practical application of Digital Twin in Industry. Providing case studies relevant to the manufacturing processes, systems, and sub-systems, this book is beneficial for both academics and industry professionals within the field of Industry 4.0 and digital manufacturing.
AISMA-2024: International Workshop on Advanced Information Security Management and Applications
This book is based on the best papers accepted for presentation during the AISMA-2024: International Workshop on Advanced in Information Security Management and Applications. The book includes research on information security problems and solutions in the field of security awareness, blockchain and cryptography, data analysis, authentication and key distribution, security incidents. The scope of research methods in information security management presents original research, including mathematical models and software implementations, related to the following topics: describing security incidents, blockchain technology, machine learning-based approaches in wireless sensor networks, phishing attack response scenarios, biometric authentication, information security audit procedures, depersonalization process. In addition, some papers focus on dynamics risks infrastructural genesis at critical information infrastructure facilities. Finally, the book gives insights into the some problems in forecasting the development of information security events. The book intends for readership specializing in the field of information security management and applications, information security methods and features.