Laxmidhar Behera

Learn More
This paper investigates new learning algorithms (LF I and LF II) based on Lyapunov function for the training of feedforward neural networks. It is observed that such algorithms have interesting parallel with the popular backpropagation (BP) algorithm where the fixed learning rate is replaced by an adaptive learning rate computed using convergence theorem(More)
We investigate the spatial distribution and the global frequency of agents who can either cooperate or defect. The agent interaction is described by a deterministic, non-iterated prisoner’s dilemma game, further each agent only locally interacts with his neighbors. Based on a detailed analysis of the local payoff structures we derive critical conditions for(More)
Extraction of predominant melody from the musical performances containing various instruments is one of the most challenging task in the field of music information retrieval and computational musicology. This paper presents a novel framework which estimates predominant vocal melody in real-time by tracking various sources with the help of harmonic clusters(More)
Existing models for document summarization mostly use the similarity between sentences in the document to extract the most salient sentences. The documents as well as the sentences are indexed using traditional term indexing measures, which do not take the context into consideration. Therefore, the sentence similarity values remain independent of the(More)
This paper concerns with intelligent stochastic filtering using the recurrent quantum neural network model. The approach does not make any assumption about the nature and shape of both signal and noise. The recurrent quantum neural network (RQNN) is designed to model the unified response of a neural lattice while ignoring the individual neuronal responses.(More)
This paper proposes an online inverse-forward adaptive scheme with a KSOM based hint generator for solving the inverse kinematic problem of a redundant manipulator. In this approach, a feed-forward network such as a radial basis function (RBF) network is used to learn the forward kinematic map of the redundant manipulator. This network is inverted using an(More)
For music transcription or musical source separation, apart from knowing the multi-F0 contours, it is also important to know which F0 has been played by which instrument. This paper focuses on this aspect, i.e. given the polyphonic audio along with its multiple F0 contours, the proposed system clusters them so as to decide 'which instrument played when.'(More)
A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning(More)