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:: Volume 8, Issue 15 (8-2021) ::
عصر برق 2021, 8(15): 70-77 Back to browse issues page
A Survey of Long Short Term Memory (LSTM) a Lgorithm and its Application
Abstract:   (1314 Views)
Recursive neural networks are a model of deep learning techniques that has been a very popular topic for the past few decades. LSTM neural networks are a new way of processing information that, because of its chain structure, operates on time-series data that leads to powerful deep learning events if LSTM is an important feature in the input sequence. Recognize in the early stages because of its short-term memory, it can transmit this information over long distances and receive and maintain such potential long-term dependencies. In this article, we have tried to examine the types of LSTM and their application in text processing in the fields of text classification, emotion analysis and feature extraction. In addition, we have also considered identifying future goals and highlighting the path of future research
Keywords: : Deep learning, Recurrent neural network LSTM, Natural language processing, Feature extraction
Full-Text [PDF 5802 kb]   (408 Downloads)    
Type of Study: Scientific-extension | Subject: Special
Received: 2021/08/2 | Accepted: 2021/08/1 | Published: 2021/08/1
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A Survey of Long Short Term Memory (LSTM) a Lgorithm and its Application. عصر برق 2021; 8 (15) :70-77
URL: http://kiaeee.ir/article-1-318-en.html


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Volume 8, Issue 15 (8-2021) Back to browse issues page
نشریه عصر برق - انجمن مهندسین برق و الکترونیک ایران - شاخه خراسان Khorasan Iranian Association of Electrical and Electronics Engineers (kiaeee)
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