Signal Processing: A Mathematical Approach, 2/e (Hardcover)
暫譯: 信號處理:數學方法,第2版 (精裝本)
Charles L. Byrne
- 出版商: CRC
- 出版日期: 2014-11-11
- 售價: $3,600
- 貴賓價: 9.5 折 $3,420
- 語言: 英文
- 頁數: 439
- 裝訂: Hardcover
- ISBN: 1482241846
- ISBN-13: 9781482241846
-
相關分類:
數位訊號處理 Dsp
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商品描述
Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics—including familiarity with Fourier series, matrices, probability, and statistics—this Second Edition:
- Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filters
- Expands the material on Fourier analysis to three new chapters to provide additional background information
- Presents real-world examples of applications that demonstrate how mathematics is used in remote sensing
Featuring problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.
商品描述(中文翻譯)
《信號處理:數學方法》旨在展示讀者所熟悉的許多數學工具如何用於理解和應用信號處理技術於實際環境中。本書假設讀者具備高年級本科或研究生水平的數學理解,包括對傅立葉級數、矩陣、機率和統計的熟悉。本書的第二版包含:
- 新增有關卷積和向量離散傅立葉變換(DFT)、平面波傳播,以及BLUE和卡爾曼濾波器的新章節
- 擴展傅立葉分析的內容,新增三個章節以提供額外的背景資訊
- 提供實際應用的範例,展示數學在遙感中的應用
《信號處理:數學方法,第二版》包含可用於課堂或練習的問題,涵蓋的主題包括一維和多維的傅立葉級數和變換;應用於聲學和電磁波傳播模型、傳輸和發射斷層成像以及影像重建;取樣和有限數據問題;矩陣方法、奇異值分解和數據壓縮;從投影中進行信號和影像重建的優化技術;自相關和功率譜;高解析度方法;檢測和最佳濾波;以及基於特徵向量的陣列處理和統計濾波、時間-頻率分析和小波的方法。
