Primer to Neuromorphic Computing

Primer to Neuromorphic Computing, 1st Edition, gathers research focused on practical applications within neuromorphic systems. Authored by Harish Garg, Jyotir Moy Chatterjee, R Sujatha, and Shatrughan Modi, this 278-page reference published by Academic Press provides a detailed overview of core concepts, including artificial intelligence, machine learning, and neuromorphic models. It establishes how specialized computational structures utilize neurons as computational units to perform processing tasks.

The text surveys active industry trends, theoretical models, and neural network hardware architectures across the field. It connects theoretical computing concepts with physical implementations, illustrating how modern hardware designs support intelligent algorithms and complex data execution models across diverse operational environments.

The book is structured for IT industry professionals, academic professors, research scholars, and system modelling and simulation experts. In addition, this reference can support elective coursework for graduate students studying advanced hardware configurations and non-traditional computing paradigms.