Prediction and Causality in Econometrics and Related Topics

Prediction and Causality in Econometrics and Related Topics Nguyen Ngoc Thach, Doan Thanh Ha, Nguyen Duc Trung, Vladik Kreinovich (Editors)
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. Categories:
Computers – Hardware
Year:
2021
Edition:
1
Publisher:
Academic Press
Language:
english
Pages:
596 / 691
ISBN 10:
012824447X
ISBN 13:
9780128244470
File:
662 MB