信号処理の数学的基礎<br>Mathematical Principles of Signal Processing : Fourier ans Wavelet Analysis (2002. XII, 289 p w. figs. 24,5 cm)

個数:

信号処理の数学的基礎
Mathematical Principles of Signal Processing : Fourier ans Wavelet Analysis (2002. XII, 289 p w. figs. 24,5 cm)

  • 提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合が若干ございます。
    2. 複数冊ご注文の場合、分割発送となる場合がございます。
    3. 美品のご指定は承りかねます。
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Hardcover:ハードカバー版/ページ数 395 p.
  • 商品コード 9780387953380

基本説明

Bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods.

Full Description

Fourier analysis is one of the most useful tools in many applied sciences. The recent developments of wavelet analysis indicates that in spite of its long history and well-established applications, the field is still one of active research.
This text bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods, while emphasizing their uses in signal processing and other applications in communications engineering. The interplay between Fourier series and Fourier transforms is at the heart of signal processing, which is couched most naturally in terms of the Dirac delta function and Lebesgue integrals.
The exposition is organized into four parts. The first is a discussion of one-dimensional Fourier theory, including the classical results on convergence and the Poisson sum formula. The second part is devoted to the mathematical foundations of signal processing - sampling,filtering, digital signal processing. Fourier analysis in Hilbert spaces is the focus of the third part, and the last part provides an introduction to wavelet analysis, time-frequency issues, and multiresolution analysis. An appendix provides the necessary background on Lebesgue integrals.

Contents

A1 Fourier Transforms of Stable Signals.- A2 Fourier Series of Locally Stable Periodic Signals.- A3 Pointwise Convergence of Fourier Series.- B1 Filtering.- B2 Sampling.- B3 Digital Signal Processing.- B4 Subband Coding.- C1 Hilbert Spaces.- C2 Complete Orthonormal Systems.- C3 Fourier Transforms of Finite-Energy Signals.- C4 Fourier Series of Finite-Power Periodic Signals.- D1 The Windowed Fourier Transform.- D2 The Wavelet Transform.- D3 Wavelet Orthonormal Expansions.- D4 Construction of an MRA.- D5 Smooth Multiresolution Analysis.- The Lebesgue Integral.- References.- Glossary of Symbols.