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Extracting inherent patterns from large data using decompositions of data matrix by a sampled subset of exemplars has found many applications in machine learning. We propose a computationally efficient algorithm for adaptive exemplar sampling, called fast exemplar selection (FES). The proposed algorithm can be seen as an efficient variant of the oASIS algorithm [1]. FES iteratively selects incoherent...
We propose a novel computationally efficient hierarchical dictionary learning (HDL) approach for data-driven unmixing and functional connectivity analysis of functional magnetic resonance imaging (fMRI) data. It is shown that by simultaneously exploiting the sparsity of the spatial brain maps and the incoherence among their evolution in time or task functions, one can achieve better performance while...
Research workers solve the simple problems of optimization by using various mathematical techniques. But to solve complex problems of optimization a stochastic and population based algorithm named Differential Evolution (DE) is used. DE is fast, simple and straightforward algorithm to optimize the problems which are complex. Like other evolutionary algorithms DE also has some drawbacks. In FBDE author...
In recent years, Wireless Sensor Networks (WSNs) have gained much attention because of its varying applications from catastrophic region to industrial and household region. In few applications, sensors are deployed in extreme environmental conditions. Hence, node access is not possible in that scenario. Therefore, a large number of sensor nodes are deployed in the target field so that node replacement...
Optimal operational & control aspects of distribution networks have been a thrust research area in academics as well as in industries since last two-three decades. In day to day practice, every one of us uses services offered by public utility distribution networks namely, water distribution network, electrical power distribution network etc. Operational topology of power distribution networks...
Deregulation in power system has a positive impact on power system planning, reliability and profit at the cost of increase in complexity in the distribution system. Several methods have been proposed to study the unbalanced three-phase load flow solution for distribution systems. Approach characterizes the network by using two matrices: the bus-injection to branch-current (BIBC) matrix and the branch-current...
In this paper, we consider the general class of coverage and clustering problems in a dynamic environment, and propose a computationally efficient framework to address them. We define the problem of achieving instantaneous coverage as a combinatorial optimization problem in a Maximum Entropy Principle framework. We then extend the framework to a dynamic environment, thereby allowing us to address...
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