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Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

- Proceedings of MDCWC 2020

About Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

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.

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  • Language:
  • English
  • ISBN:
  • 9789811602887
  • Binding:
  • Hardback
  • Pages:
  • 643
  • Published:
  • May 28, 2021
  • Edition:
  • 12021
  • Dimensions:
  • 155x235x0 mm.
  • Weight:
  • 1154 g.
Delivery: 2-3 weeks
Expected delivery: January 26, 2025

Description of Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

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.

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