Quantum Inspired Computational Intelligence
1st Edition
Research and Applications
Description
Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence—or soft computing—is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information.
Key Features
- Brings together quantum computing with computational intelligence to achieve enhanced performance and robust solutions
- Includes numerous case studies, tools, and technologies to apply the concepts to real world practice
- Provides the missing link between the research and practice
Readership
Academic and corporate researchers in artificial intelligence, computational intelligence, applied computing, data science, data mining, signal processing, pattern recognition, machine learning, and quantum computing
Table of Contents
Chapter 1: Quantum Neural Computation of Entanglement is Robust to Noise and Decoherence
Chapter 2: Quantum Computing and Supervised Machine Learning: Training, Model Selection and Error Estimation
Chapter 3: Field Computation: A Framework for Quantum Inspired Computing
Chapter 4 : Design of Cellular Quantum-inspired Evolutionary Algorithm with Random Topologies
Chapter 5 :An Efficient Pure Color Image Denoising using Quantum Parallel Bi-Directional Self-Organizing Neural Network Architecture
Chapter 6: Quantum Inspired Multi-objective SA for Bi-level Image Thresholding
Chapter 7: Quantum Inspired Computational Intelligent Techniques in Image Segmentation
Chapter 8: Fuzzy Evaluated Quantum Cellular Automata Approach for Watershed Image Analysis
Chapter 9: Quantum Inspired Evolutionary Algorithm for Scaling Factors Optimization during Manifold Medical Information Embedding
Chapter 10: Digital Filter Design using Quantum Inspired Multi-Objective Cat Swarm Optimization Algorithm
Chapter 11: A Novel Graph Clustering Algorithm Based On Discrete Time Quantum Random Walk
Chapter 12: Schrodinger equation as an inspiration for client portfolio simulation hybrid system based on dynamic Bayesian networks and REFII model
Chapter 13: A Quantum Inspired Hybrid Intelligent Position Monitoring System in Wireless Networks
Details
- No. of pages:
- 506
- Language:
- English
- Copyright:
- © Morgan Kaufmann 2017
- Published:
- 15th September 2016
- Imprint:
- Morgan Kaufmann
- eBook ISBN:
- 9780128044377
- Paperback ISBN:
- 9780128044094
About the Author
Siddhartha Bhattacharyya
Dr. Siddhartha Bhattacharyya [SMIEEE, SMACM, MIRSS, MIAENG, MACSE, MIAASSE, LMCSI, LMOSI, LMCEGR] is Professor and Head of Information Technology of RCC Institute of Information Technology, Kolkata, India. In addition, he is serving as the Dean of Research and Development of the institute from November 2013. Dr. Bhattacharyya did his Bachelors in Physics, Bachelors in Optics and Optoelectronics and Masters in Optics and Optoelectronics from University of Calcutta, India in 1995, 1998 and 2000 respectively. He completed PhD in Computer Science and Engineering from Jadavpur University, India in 2008. He is the recipient of the University Gold Medal from the University of Calcutta for his Masters.His research interests include soft computing, pattern recognition, multimedia data processing, hybrid intelligence and quantum computing.
Affiliations and Expertise
RCC Institute of Information Technology, Kolkata, India
Ujjwal Maulik
Dr. Ujjwal Maulik is a Professor in the Department of Computer Science and Engineering, Jadavpur University, Kolkata, India since 2004. He is co-author of seven books for Springer and Wiley, more than 250 research publications, and Associate Editor of IEEE Transaction on Fuzzy Systems and Information Sciences. His research interests include computational intelligence, bioinformatics, combinatorial optimization, pattern recognition, and data mining.
Affiliations and Expertise
Jadavpur University, Kolkata, India
Paramartha Dutta
Dr. Paramartha Dutta did his Bachelors and Masters in Statistics from the Indian Statistical Institute, Calcutta in the years 1988 and 1990 respectively. He afterwards completed his Master of Technology in Computer science from the same Institute in the year 1993 and Doctor of Philosophy in Engineering from the Bengal Engineering and Science University, Shibpur in 2005 respectively. He has served in the capacity of research personnel in various projects funded by Govt. of India, which include DRDO, CSIR, Indian Statistical Institute, Calcutta etc. Dr. Dutta is now a Professor in the Department of Computer and system Sciences of the Visva Bharati University, West Bengal, India. Prior to this, he served Kalyani Government Engineering College and College of Engineering in West Bengal as full time faculty members. He has coauthored four books and has also one edited book to his credit. He has published
about hundred fifty papers in various journals and conference proceedings, both international and national. Presently, he is supervising four students for their Ph. D program registered with Visva Bharati University and West Bengal University of Technology. Dr. Dutta is a Life Fellow of the Optical Society of India (OSI), Computer Society of India (CSI), Indian Science Congress Association (ISCA), Indian Society for Technical Education (ISTE), Indian Unit of Pattern Recognition and Artificial Intelligence (IUPRAI) - the Indian affiliate of the International Association for Pattern Recognition (IAPR), Senior Member of Associated Computing Machinery (ACM), IEEE Computer Society, USA and IACSIT.
Affiliations and Expertise
Visva Bharati University, West Bengal, India