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Machine learning, deep learning and ...

Gopi, E. S.

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Machine learning, deep learning and computational intelligence for wireless communication = proceedings of MDCWC 2020 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning, deep learning and computational intelligence for wireless communication/ edited by E. S. Gopi.
其他題名:	proceedings of MDCWC 2020 /
其他題名:	MDCWC 2020
其他作者:	Gopi, E. S.
團體作者:	MDCWC (Conference)
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	xix, 643 p. :ill. (some col.), digital ;24 cm.
內容註:	Deep Learning to Predict the Number of Antennas in a Massive MIMO Setup based on Channel Characteristics -- Optimal Design of Fractional Order PID Controller for AVR System using Black Widow Optimization (BWO) Algorithm -- LSTM Network for Hotspot Prediction in Traffic Density of Cellular Network -- Generative Adversarial Network and Reinforcement Learning to Estimate Channel Coefficients -- Self-Interference Cancellation in Full-duplex Radios for 5G Wireless Technology using Neural Network -- Dimensionality Reduction of KDD-99 using Self-perpetuating Algorithm -- Energy Efficient Neigbour Discovery using Bacterial Foraging Optimization (BFO) Technique for Asynchronous Wireless Sensor Networks -- LSTM based Outlier Detection Method for WSNs -- An Improved Swarm Optimization Algorithm based Harmonics Estimation and Optimal Switching Angle Identification -- A Study of Ensemble Methods for Classification.
Contained By:	Springer Nature eBook
標題:	Machine learning - Congresses. -
電子資源:	https://doi.org/10.1007/978-981-16-0289-4
ISBN:	9789811602894

Machine learning, deep learning and computational intelligence for wireless communication = proceedings of MDCWC 2020 /
Machine learning, deep learning and computational intelligence for wireless communicationproceedings of MDCWC 2020 /[electronic resource] :MDCWC 2020edited by E. S. Gopi. - Singapore :Springer Singapore :2021. - xix, 643 p. :ill. (some col.), digital ;24 cm. - Lecture notes in electrical engineering,v.7491876-1100 ;. - Lecture notes in electrical engineering ;v.749..

Deep Learning to Predict the Number of Antennas in a Massive MIMO Setup based on Channel Characteristics -- Optimal Design of Fractional Order PID Controller for AVR System using Black Widow Optimization (BWO) Algorithm -- LSTM Network for Hotspot Prediction in Traffic Density of Cellular Network -- Generative Adversarial Network and Reinforcement Learning to Estimate Channel Coefficients -- Self-Interference Cancellation in Full-duplex Radios for 5G Wireless Technology using Neural Network -- Dimensionality Reduction of KDD-99 using Self-perpetuating Algorithm -- Energy Efficient Neigbour Discovery using Bacterial Foraging Optimization (BFO) Technique for Asynchronous Wireless Sensor Networks -- LSTM based Outlier Detection Method for WSNs -- An Improved Swarm Optimization Algorithm based Harmonics Estimation and Optimal Switching Angle Identification -- A Study of Ensemble Methods for Classification.

This book is a collection of best selected research papers presented at the Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2020) held during October 22nd to 24th 2020, at the Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli, India. The presented papers are grouped under the following topics (a) Machine Learning, Deep learning and Computational intelligence algorithms (b)Wireless communication systems and (c) Mobile data applications and are included in the book. The topics include the latest research and results in the areas of network prediction, traffic classification, call detail record mining, mobile health care, mobile pattern recognition, natural language processing, automatic speech processing, mobility analysis, indoor localization, wireless sensor networks (WSN), energy minimization, routing, scheduling, resource allocation, multiple access, power control, malware detection, cyber security, flooding attacks detection, mobile apps sniffing, MIMO detection, signal detection in MIMO-OFDM, modulation recognition, channel estimation, MIMO nonlinear equalization, super-resolution channel and direction-of-arrival estimation. The book is a rich reference material for academia and industry.

ISBN: 9789811602894

Standard No.: 10.1007/978-981-16-0289-4doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5 / .M33 2020

Dewey Class. No.: 006.31

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