This book presents selected papers from the International Conference on Computing, Communication, Electrical and Biomedical Systems (ICCCEBS 2021), held in March 2021 at KPR College of Engineering and Technology, Coimbatore, Tamil Nadu, India. The conference explores the interface between industry and real-time environments with newly developed techniques in computing and communications engineering. The papers describe results of conceptual, constructive, empirical, experimental, and theoretical work in areas of computing, communication, electrical, and biomedical systems. Contributors include academic scientists, researchers, industry representatives, postdoctoral fellows, and research scholars from around the world.

Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.

This book presents selected papers from the International Conference on Computing, Communication, Electrical and Biomedical Systems (ICCCEBS 2021), held in March 2021 at KPR College of Engineering and Technology, Coimbatore, Tamil Nadu, India. The conference explores the interface between industry and real-time environments with newly developed techniques in computing and communications engineering. The papers describe results of conceptual, constructive, empirical, experimental, and theoretical work in areas of computing, communication, electrical, and biomedical systems. Contributors include academic scientists, researchers, industry representatives, postdoctoral fellows, and research scholars from around the world.

The brain-computer interface (BCI) is an emerging technology that is developing to be more functional in practice. The aim is to establish, through experiences with electronic devices, a communication channel bridging the human neural networks within the brain to the external world. For example, creating communication or control applications for locked-in patients who have no control over their bodies will be one such use. Recently, from communication to marketing, recovery, care, mental state monitoring, and entertainment, the possible application areas have been expanding. Machine learning algorithms have advanced BCI technology in the last few decades, and in the sense of classification accuracy, performance standards have been greatly improved. For BCI to be effective in the real-world, however some problems remain to be solved. It is anticipated that research focusing on new development that would bring solutions in this regard. Deep learning has been applied in various fields such as computer vision and natural language processing, along with BCI growth, outperforming conventional approaches to machine learning. As a result, a significant number of researchers have shown interest in deep learning in engineering, technology, and other industries; convolutional neural network (CNN), recurrent neural network (RNN), and generative adversarial network (GAN).