Convex optimization in signal and image processing signal. Realtime convex optimization in signal processing ieee. Perhaps more exciting is the possibility that convex optimization can be embedded directly in signal processing algorithms that run online, with strict real time deadlines, even at rates of tens. Real time convex optimization in signal processing. Parallel and distributed successive convex approximation methods. In particular, automatic code generation makes it easier to create convex optimization solvers that are made much faster by being designed for a specific problem family. Operation and configuration of a storage portfolio via convex. Convex optimization has a long history in signal processing, dating back to the 1960s. The first is the problem of operating a portfolio of storage devices in realtime, i. Boyd, realtime convex optimization in signal processing, ieee signal processing magazine, 273. Convex optimization has been used in signal processing for a long time, to choose coefficients for use in fast linear algorithms, such as in filter or array design. From fundamentals to applications provides fundamental background knowledge of convex optimization, while striking a balance between mathematical theory and applications in signal processing and communications in addition to comprehensive proofs and perspective interpretations for core convex optimization theory, this. Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets.
The disciplined convex programming framework that has been shown useful in transforming problems to a standard. Realtime convex optimization in signal processing ieee xplore. Emphasis on cuttingedge research and formulating problems in convex form make this an ideal textbook for advanced graduate courses and a useful selfstudy. The history is described below in a little more detail. This book, written by a team of leading experts, sets out the theoretical underpinnings of the subject and provides tutorials on a wide range of convex optimization applications. Emphasis throughout is on cuttingedge research and on formulating problems in convex form, making this an ideal textbook for advanced graduate courses and a. Cooperative distributed multiagent optimization figure 1. From fundamentals to applications provides fundamental background knowledge of convex optimization, while striking a balance between mathematical theory and applications in signal processing and communications in addition to comprehensive proofs and perspective interpretations for core convex optimization theory, this book also. Real time convex optimization in signal processing abstract. Theres a whole area of signal processing dedicated to optimal filtering. Realtime convex optimization in signal processing, j. Convex optimization guide books acm digital library.
1155 1211 167 1167 1563 94 1561 1481 1048 1009 915 796 183 1057 704 821 1240 772 611 1341 1242 1132 663 709 290 1113 892 461 315 183 980 1163 60 170 1166 144 812 1232 181 458 361 320 1068 204 241 59 680