Current Trends in Signal Processing
Volume 9, Issue 3 (2019)
Published
Table of contents
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Comparative Analysis of Neural Network and Linear Regression Applied to Black Friday Data
Abstract: AbstractIn this study, it compares two different types of neural networks. First is a single layer neural network and other is multiple hidden layer neural network. For just comparisons it is ensured that both uses the same activation and output functions and have the same number of nodes and parameters. The networks are trained by the gradient descent algorithm to approximate linear and quadratic functions and examine their convergence properties. …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 1–4 Read article
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Segments to Evaluate Remote Sensing Imagery
Abstract: AbstractSegmentation is scheme to rely accused formation by unconventional modeling. This is first step to increase resolution of as object specific formation. Petitioning to scale is algorithmic segmented binary pixel grouping between two subjectively heterotypic forms. Nevertheless noise free has favored grouping of pixels so as comparable to real object. Parameters for segment scale are typified shape like cube or circle, color, compactness and growth of image when subjected towards …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 19–22 Read article
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Power Quality Issues and Mitigation Strategies: A Review
Abstract: AbstractTo protect the power system recognition and arrangement of voltage (V) and current (I) issues are essential tasks. Most power quality (PQ) disturbances are unstable and ephemeral; the call for recognition and arrangement of voltages and current is proved. There are some intelligent system technologies which have dominance regarding fault analysis by using wavelet transform (WT), expert systems and artificial neural networks. As signals are classified in six classes: five …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 23–27 Read article
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Remote Sensing Accession from Imagery
Abstract: AbstractRemote sensing (RS) apt scaled from balloon-aided physical camera to multispectral regime after exploring of hyperspectral sensors made of integrated circuits. Device prosecutions to segment-wise deduction has studied to scale point to point explore. Multi-aspect in any consideration explored hyper-linking for any consideration. Band explore by sensors achieves coarse-to-fine adjustments for any investigation. Atmospheric absorption of linking radiant energy has subjected to incorporate additional algorithm to claim actual of actuals …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 5–8p Read article
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Fuzzy Variable Frame Analysis for Speech Recognition
Abstract: AbstractRecent works in machine learning has focused on models such as support vector machine (SVM), artificial neural network (ANN) and long short-term memory (LSTM), for automatically controlling the generalization and parameterization of the optimization process. This paper presents a fuzzy interpretation frame analysis procedure using LSTM classifier for noisy speech at word level using thresholding and local maxima procedure at framing level for the recognition process. Front end MFCC procedure …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 9–18 Read article