Tensors for Data Processing - by Yipeng Liu (Paperback)
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Highlights
- Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing.
- Author(s): Yipeng Liu
- 596 Pages
- Technology, Signals & Signal Processing
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Book Synopsis
Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods.
As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry.
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Q: Who is the target audience for this book?
A: This reference is aimed at students, researchers, and industry developers in fields related to data processing.
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Q: What topics does this book cover regarding tensor computation?
A: The book discusses computation theories, processing methods, and applications in data processing using tensors.
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Q: Is this book suitable for beginners in the subject?
A: This book is designed for those with a foundational understanding, as it delves into advanced tensor methods.
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Q: What are the benefits of tensor-based processing over matrices?
A: Tensor-based processing prevents multi-linear data structure loss that occurs in classical matrix methods.
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Q: In which fields can tensor-based methods be applied?
A: Applications include signal processing, computer science, neuroscience, medical engineering, and more.
submitted byAI Shopping Assistant - 29 days agoAi generated