Complex-Valued Neural Networks: Advances and Applications (Hardcover)
暫譯: 複數值神經網絡:進展與應用(精裝版)
Akira Hirose
- 出版商: IEEE
- 出版日期: 2013-04-29
- 售價: $4,550
- 貴賓價: 9.5 折 $4,323
- 語言: 英文
- 頁數: 304
- 裝訂: Hardcover
- ISBN: 111834460X
- ISBN-13: 9781118344606
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相關分類:
DeepLearning
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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)
介紹複數值神經網絡的最新進展,並展示其在廣泛應用中的理論
複數值神經網絡是一種快速發展的神經網絡框架,利用複數運算,展現出其在學習、自組織和處理動態方面的特定特徵。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波、光波、聲波/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關鍵優勢,因為信號通常在時間/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 涵蓋了圍繞這一及時主題的前沿話題和應用。該書展示了先進理論及其在通信系統、圖像處理系統和腦機介面等廣泛應用中的應用,提供了全面的內容,包括:
- 傳統複數值神經網絡
- 四元數神經網絡
- 克利福德代數神經網絡
由該領域的國際專家呈現的 複數值神經網絡:進展與應用 非常適合對計算智能、人工智能、機器學習理論和算法感興趣的高級計算智能理論家、電磁理論家和數學家。
