theory and practice of recursive identification 第四章的中文翻译

MIT DIMITRI BERTSEKAS教授的Convex Optimization Theory 课程PPT,教材详细摘要和教材习题解答等。

再次奉献一本PLC的国外经典教材 共1047页 这是由外国友人提供的 国内是买不到也无法下载的 适用于有一定基础的专业工程师

The Theory and Practice of Revenue Management is a book that comprehensively covers theory and practice of the entire field, including both quantity and price-based RM, as well as significant coverage of supporting topics such as forecasting and economics.

This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging. Sparse and Redundant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing. * Introduces theoretical and numerical foundations before tackling applications * Discusses how to use the proper model for various situations * Introduces sparse and redundant representations * Focuses on applications in signal and image processing The field of sparse and redundant representation modeling has gone through a major revolution in the past two decades. This started with a series of algorithms for approximating the sparsest solutions of linear systems of equations, later to be followed by surprising theoretical results that guarantee these algorithms’ performance. With these contributions in place, major barriers in making this model practical and applicable were removed, and sparsity and redundancy became central, leading to state-of-the-art results in various disciplines. One of the main beneficiaries of this progress is the field of image processing, where this model has been shown to lead to unprecedented performance in various applications. This book provides a comprehensive view of the topic of sparse and redundant representation modeling, and its use in signal and image processing. It offers a systematic and ordered exposure to the theoretical foundations of this data model, the numerical aspec

Manifold learning theory and applications清晰版(英文).pdf。 注：版权归作者所有，请购买正版。 亚马逊价格：686.90/RMB

fundamentals-of-statistical-signal-processing-volume-i-estimation-theory_1

This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way that instils a deep understanding of the relevant mathematical principles, and develops an intuitive grasp of the way these principles can be applied to modelling real-world systems. It includes a careful review of elementary probability and detailed coverage of Poisson, Gaussian and Markov processes with richly varied queuing applications. The theory and applications of inference, hypothesis testing, estimation, random walks, large deviations, martingales and investments are developed. Written by one of the world's leading information theorists, evolving over twenty years of graduate classroom teaching and enriched by over 300 exercises, this is an exceptional resource for anyone looking to develop their understanding of stochastic processes.

Fundamentals of statistical signal processing: estimation theory的英文版，但是影印版，总共595页，清晰度还可以，希望能对需要的人有帮组

非常经典的矩阵扰动理论教材和参考书。可用djvu阅读器打开.