Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing
Tripathy, Rajesh Kumar, Pachori, Ram Bilas
- 出版商: Academic Press
- 出版日期: 2024-06-18
- 售價: $6,300
- 貴賓價: 9.5 折 $5,985
- 語言: 英文
- 頁數: 184
- 裝訂: Quality Paper - also called trade paper
- ISBN: 044314141X
- ISBN-13: 9780443141416
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相關分類:
Machine Learning
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商品描述
Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular data analysis. Topics in this book include machine learning methods such as supervised learning, unsupervised learning, semi-supervised learning, and meta-learning combined with different signal processing techniques such as multivariate data analysis, time-frequency analysis, multiscale analysis, and feature extraction techniques for the detection of cardiovascular diseases, heart valve disorders, hypertension, and activity monitoring using ECG, PPG, and PCG signals. In addition, this book also includes the applications of digital signal processing (time-frequency analysis, multiscale decomposition, feature extraction, non-linear analysis, and transform domain methods), machine learning and deep learning (convolutional neural network (CNN), recurrent neural network (RNN), transformer and attention-based models, etc.) techniques for the analysis of cardiac signals. The interpretable machine learning and deep learning models combined with signal processing for cardiovascular data analysis are also covered.
商品描述(中文翻譯)
《信號處理驅動的機器學習技術於心血管數據處理》介紹了機器學習的最新進展,並結合了基於信號處理的新方法來分析心血管數據。本書的主題包括機器學習方法,如監督學習、非監督學習、半監督學習和元學習,並結合不同的信號處理技術,如多變量數據分析、時頻分析、多尺度分析和特徵提取技術,用於檢測心血管疾病、心臟瓣膜疾病、高血壓以及使用ECG、PPG和PCG信號進行的活動監測。
此外,本書還包括數位信號處理(時頻分析、多尺度分解、特徵提取、非線性分析和變換域方法)、機器學習和深度學習(卷積神經網絡(CNN)、遞迴神經網絡(RNN)、變壓器和基於注意力的模型等)技術在心臟信號分析中的應用。可解釋的機器學習和深度學習模型結合信號處理進行心血管數據分析的內容也有涵蓋。