Signal Processing in Medicine and Biology: Innovations in Big Data Processing (醫學與生物信號處理：大數據處理的創新)

《醫學與生物學中的信號處理：大數據處理的創新》提供了一個跨學科的視角，探討生物醫學信號處理的最先進創新，特別是其在大型數據集和機器學習中的應用。各章節提供詳細的數學推導和完整的實作細節，使讀者能夠完全掌握這些技術。本書展示了成功應用的教程和範例，將吸引對信號處理、醫學和生物學在醫療、工程和計算機科學交匯處的應用感興趣的各類專業人士、研究人員和學生。

​Iyad Obeid, Ph.D., is an associate professor of Electrical and Computer Engineering at Temple University with a secondary appointment in the Department of Bioengineering. His research interests include neural signal processing, biomedical signal processing, and medical instrumentation. His research in these fields has been funded by NIH, NSF, DARPA, and the US Army. Together with Dr. Joseph Picone, he is the co-founder of the Neural Engineering Data Consortium, whose goal is to provide large, well-curated neural signal data to the biomedical research community. In addition to earlier work on brain-machine interfaces, Dr. Obeid's current research has expanded to include non-parametric unsupervised machine learning as well as concussion and injury assessment instrumentation built using commercial off-the-shelf sensors.
Joseph Picone, Ph.D., is a professor of Electrical and Computer Engineering at Temple University, where he directs the Institute for Signal and Information Processing and is the Associate Director of the Neural Engineering Data Consortium. His primary expertise is in statistical modeling with applications in signal processing, specifically acoustic modeling in speech recognition. A common theme throughout his research career has been a focus on fundamentally new statistical modeling paradigms. He has been an active researcher in various aspects of speech processing for over 35 years. He currently collaborates with the Temple School of Medicine and has previously collaborated with many academic institutions (e.g., the Linguistic Data Consortium, Johns Hopkins University), government agencies (e.g., Department of Defense, DARPA), and companies (e.g., MITRE, Texas Instruments). The National Science Foundation, DoD, DARPA, and several commercial interests have funded his research. He has published over 200 technical papers and holds eight patents.
Ivan Selesnick, Ph.D., is a professorof Electrical and Computer Engineering at the New York University Tandon School of Engineering. He received the BS, MEE, and Ph.D. degrees in Electrical Engineering from Rice University, and joined Polytechnic University in 1997 (now NYU Tandon School of Engineering). He received an Alexander von Humboldt Fellowship in 1997 and a National Science Foundation Career award in 1999. In 2003, he received the Jacobs Excellence in Education Award from Polytechnic University. Dr. Selesnick's research interests are in signal and image processing, wavelet-based signal processing, sparsity techniques, and biomedical signal processing. He became an IEEE Fellow in 2016 and has been an associate editor for the IEEE Transactions on Image Processing, IEEE Signal Processing Letters, IEEE Transactions on Signal Processing, and IEEE Transactions on Computational Imaging.

Iyad Obeid, Ph.D.，是天普大學電機與計算機工程系的副教授，並在生物工程系擔任兼任職位。他的研究興趣包括神經信號處理、生物醫學信號處理和醫療儀器。他在這些領域的研究得到了國立衛生研究院（NIH）、國家科學基金會（NSF）、國防高級研究計畫局（DARPA）和美國陸軍的資助。與Joseph Picone博士共同創立了神經工程數據聯盟，該聯盟的目標是為生物醫學研究社群提供大量經過良好策劃的神經信號數據。除了早期在腦機介面方面的工作外，Obeid博士目前的研究已擴展到包括非參數無監督機器學習，以及使用商用現成傳感器構建的腦震盪和傷害評估儀器。

Joseph Picone, Ph.D.，是天普大學電機與計算機工程系的教授，並擔任信號與信息處理研究所的主任，以及神經工程數據聯盟的副主任。他的主要專長在於統計建模，應用於信號處理，特別是在語音識別中的聲學建模。他的研究生涯中一個共同主題是專注於根本新的統計建模範式。他在語音處理的各個方面活躍研究超過35年。目前，他與天普醫學院合作，並曾與許多學術機構（例如語言數據聯盟、約翰霍普金斯大學）、政府機構（例如國防部、DARPA）和公司（例如MITRE、德州儀器）合作。國家科學基金會、國防部、DARPA和幾個商業機構資助了他的研究。他已發表超過200篇技術論文並擁有八項專利。

Ivan Selesnick, Ph.D.，是紐約大學坦登工程學院的電機與計算機工程系教授。他在萊斯大學獲得電機工程的學士、碩士和博士學位，並於1997年加入理工學院（現為紐約大學坦登工程學院）。他於1997年獲得亞歷山大·馮·洪堡獎學金，並於1999年獲得國家科學基金會的職業獎。在2003年，他獲得理工學院的雅各布斯教育卓越獎。Selesnick博士的研究興趣包括信號與影像處理、基於小波的信號處理、稀疏技術和生物醫學信號處理。他於2016年成為IEEE Fellow，並擔任過《IEEE影像處理期刊》、《IEEE信號處理快報》、《IEEE信號處理期刊》和《IEEE計算影像期刊》的副編輯。