Prof.  Manu Pratap  Singh
Dr. B. R. Ambedkar University,  India

Title: Pattern Classification Using Quantum Neural Networks : A novel Approach in Machine learning

Abstract:

There are various methods have been proposed for Pattern classifications with quantum neural networks. Mostly these methods are employing the Grover’s iteration on Bell’s MES in two-qubit system.  Further has been demonstrated that for any pattern classification in a two-qubit system the maximally entangled states of Singh-Rajput eigen basis provide the most suitable choice of search states and in no case any of Bell’s states is suitable for such pattern classifications. Here in this present work we are employing the quantum perceptron architecture which incorporates entanglement of weights and states both for producing the required pattern classification. The quantum perceptron learning rule is presented to train the network for the given training set and convergence and normalization of weights have been observed. The simulation results show that the proposed quantum perceptron neural network is capable to classify all the kinds of patterns whether the patterns are linearly separable or not.  

Keywords: Quantum neural networks, Machine learning, Pattern classification, Quantum information processing, Entanglement.

Biography:

Prof. Manu Pratap Singh received his Ph.D. from Kumaun University Nainital, Uthrakhand, India, in 2001. He completed his Master of Science in Computer Science from Allahabad University, Allahabad in 1995. He is currently working as Professor in Department of Computer Science, Institute of Engineering and Technology, Dr. B.R. Ambedkar University, Agra, UP, India since 2014. He is engaged in teaching and research since last 20 years. He has more than 90 research papers in journals of international and national repute. His work has been recognized widely around the world in the form of citations of his research papers. He also has received the Young Scientist Award in computer science by international Academy of Physical sciences, Allahabad in year 2005. He has guided 18 students for their doctorate in computer science. He is also referee of various international and national journals like International Journal of Uncertainty, Fuzziness and Knowledge Based Systems published by World scientific publishing cooperation Ltd, International Journal of Engineering, Iran, IEEE Transaction of fuzzy systems and European journal of operation research published by Elsevier. He has developed a feed forward neural networks simulator for hand written character recognition of English alphabets. He has also developed a hybrid evolutionary algorithm for hand written character recognition of English as well as for Hindi language classification. In his hybrid approach the Genetic algorithm is incorporated with back propagation learning rule to train the feed forward neural networks. In this approach the genetic algorithm starts from the suboptimal solution and converges for the optimal solutions. This approach leads for the multi objective optimization phenomena. Another hybrid approach of evolutionary algorithm has been developed for the feedback neural network of Hopfield type for efficient recalling for the memorized patterns. Here also the randomness from the genetic algorithm is minimized by starting it from the suboptimal solution in the term of parent weight matrix for the global optimal solutions i.e. correct weight matrices for the network to consider it for efficient pattern recalling.  His research interests are focused on Neural networks, pattern recognition and machine intelligence, soft-computing, quantum computing etc. He is a member of technical committee of IASTED, Canada since 2004. He is also the regular member of machine intelligence Research Labs (MIR Labs), scientific network for innovation and research excellence (SNIRE), Auburn, Washington, USE, http://www.mirlabs.org, since 2012. His Google citation indices are h-14, i10-index is 16 and he has 434 citations. He has been invited as keynote speaker and invited guest speaker in various institutions in India and Abroad.