Complex-Valued Neural Networks: Advances and Applications (Hardcover)

Akira Hirose

  • 出版商: IEEE
  • 出版日期: 2013-04-29
  • 定價: $4,550
  • 售價: 9.0$4,095
  • 語言: 英文
  • 頁數: 304
  • 裝訂: Hardcover
  • ISBN: 111834460X
  • ISBN-13: 9781118344606
  • 相關分類: 人工智慧物理學 Physics
  • 立即出貨 (庫存=1)

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商品描述

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications

Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and superconducting waves. This fact is a critical advantage in practical applications in diverse fields of engineering, where signals are routinely analyzed and processed in time/space, frequency, and phase domains.

Complex-Valued Neural Networks: Advances and Applications covers cutting-edge topics and applications surrounding this timely subject. Demonstrating advanced theories with a wide range of applications, including communication systems, image processing systems, and brain-computer interfaces, this text offers comprehensive coverage of:

  • Conventional complex-valued neural networks
  • Quaternionic neural networks
  • Clifford-algebraic neural networks

Presented by international experts in the field, Complex-Valued Neural Networks: Advances and Applications is ideal for advanced-level computational intelligence theorists, electromagnetic theorists, and mathematicians interested in computational intelligence, artificial intelligence, machine learning theories, and algorithms.

商品描述(中文翻譯)

本書介紹了複數值神經網絡的最新進展,並通過在各種應用中展示理論來加以證明。

複數值神經網絡是一種快速發展的神經網絡框架,利用複數算術,在學習、自組織和處理動態中展示出特定的特性。它們非常適合處理由振幅和相位組成的複數振幅,這是物理系統中處理電磁、光、聲/超聲波以及量子波(即電子和超導波)的核心概念之一。這一事實在工程的各個領域中具有重要的優勢,其中信號通常在時間/空間、頻率和相位域中進行分析和處理。

《複數值神經網絡:進展與應用》涵蓋了這一及時主題周圍的尖端議題和應用。本書展示了包括通信系統、圖像處理系統和腦-電腦界面在內的各種應用中的先進理論,全面介紹了:

- 傳統的複數值神經網絡
- 四元數神經網絡
- 克利福德代數神經網絡

本書由國際領域專家提供,非常適合高級計算智能理論家、電磁理論家和對計算智能、人工智能、機器學習理論和算法感興趣的數學家閱讀。