Unit 6 Introduction to Digital Signal Processing exercises 上海海事大学信息工程学院

Exercises1: Recent Advances in Signal Processing The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability(易处理的) over real-world accuracy. These constraints were imposed（受限制） by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering.

Background This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity.

Exercises2: Introduction to journal, Digital Signal Processing: A review Journal Digital Signal Processing: a Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative one. The journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of groundbreaking research in signal processing with both academic and industrial appeal.

Exercises2: The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging areas in signal processing which do not find space in other journals of the field. These include: environmental signal processing, stochastic modelling of biological and chemical processes, Seismic（地震的） signal processing, financial time series analysis, stochastic calculus,

Exercises2: Geophysical（地球物理学） signal processing, systems biology, Chemioinformatics （化学信息学）, signal processing for human-computer interaction and intelligent user interfaces, signal processing for audio, visual and performance arts, signal processing for disaster management and prevention, signal processing for renewable energy, game theory and group theory for signal processing, information theory articles with a signal processing perspective.

Exercises2: Papers in the classical application areas of signal processing such as telecommunications, speech and image processing are welcome only if they contain novel research. Purely application oriented articles in these areas should be submitted to the relevant dedicated journals. Similarly, authors who would like to submit on areas of neural networks or fuzzy sets are invited to submit their work to the appropriate journals.

Exercises2: Digital Signal Processing: a Review Journal also aims to publish at least one high quality review article in every issue and to provide focus issues with special emphasis on emerging topics. Discussion articles in which several leading researchers discuss the future of a specific research area are also welcome.

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