Deep Learning in Time Series Analysis
暫譯: 時間序列分析中的深度學習
Gharehbaghi, Arash
- 出版商: CRC
- 出版日期: 2025-04-13
- 售價: $2,970
- 貴賓價: 9.5 折 $2,822
- 語言: 英文
- 頁數: 196
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1032418869
- ISBN-13: 9781032418865
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
商品描述
The concept of deep machine learning is easier to understand by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the cycle-to-cycle variations.
商品描述(中文翻譯)
深度機器學習的概念可以透過關注循環隨機時間序列來更容易理解，這些時間序列的內容不僅在循環內部是非平穩的，還在循環之間的變化中也是非平穩的。
作者簡介
Arash Gharehbaghi obtained a M.Sc. degree in biomedical engineering from Amir Kabir University, Tehran, Iran, in 2000, an advanced M.Sc. of Telemedia from Mons University, Belgium, and PhD degree of biomedical engineering from Linköping University, Sweden in 2014. He is a researcher at the School of Information Technology, Halmstad University, Sweden. He has conducted several studies on signal processing, machine learning and artificial intelligence over two decades that led to the international patents, and publications in high prestigious scientific journals.
He has proposed new learning methods for learning and validating time series analysis, among which Time-Growing Neural Network, and A-Test are two recent ones that have interested the machine learning community. He won the first prize of young investigator award from the International Federation of Biomedical Engineering in 2014.
作者簡介(中文翻譯)
Arash Gharehbaghi 於2000年在伊朗德黑蘭的阿米爾卡比爾科技大學獲得生物醫學工程碩士學位，隨後在比利時的蒙斯大學獲得高級碩士學位，並於2014年在瑞典林雪平大學獲得生物醫學工程博士學位。他目前是瑞典哈爾姆斯塔德大學資訊科技學院的研究員。在過去二十年中，他在信號處理、機器學習和人工智慧方面進行了多項研究，並獲得了國際專利及在高水平科學期刊上發表的論文。
他提出了新的學習方法來學習和驗證時間序列分析，其中「時間增長神經網絡」(Time-Growing Neural Network) 和「A-Test」是最近引起機器學習社群興趣的兩個方法。他於2014年獲得國際生物醫學工程聯合會的青年研究者獎第一名。
