Dimensionality reduction techniques are used to reduce the complexity for analysis of high-dimensional data sets. The raw input data set may have large dimensions, and it might consume time and lead to wrong predictions if unnecessary data attributes are been considered for analysis. Hence, using dimensionality reduction techniques, one can reduce the dimensions of input data toward accurate prediction with less cost. In this paper, the different machine learning approaches used for dimensionality reductions such as principal component analysis (PCA), singular value decomposition, linear discriminant analysis, Kernel PCA, and artificial neural network have been studied.

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Objective: The prospective need of SIMD (Single Instruction and Multiple Data) applications like video and image processing in single system requires greater flexibility in computation to deliver high quality real time data. This paper performs an analysis of FPGA (Field Programmable Gate Array) based high performance Reconfigurable OpenRISC1200 (ROR) soft-core processor for SIMD.Methods: The ROR1200 ensures performance improvement by data level parallelism executing SIMD instruction simultaneously in HPRC (High Performance Reconfigurable Computing) at reduced resource utilization through RRF (Reconfigurable Register File) with multiple core functionalities. This work aims at analyzing the functionality of the reconfigurable architecture, by illustrating the implementation of two different image processing operations such as image convolution and image quality improvement. The MAC (Multiply-Accumulate) unit of ROR1200 used to perform image convolution and execution unit with HPRC is used for image quality improvement.Result: With parallel execution in multi-core, the proposed processor improves image quality by doubling the frame rate up-to 60 fps (frames per second) with peak power consumption of 400mWatt. Thus the processor gives a significant computational cost of 12ms with a refresh rate of 60Hz and 1.29ns of MAC critical path delay.Conclusion:This FPGA based processor becomes a feasible solution for portable embedded SIMD based applications which need high performance at reduced power consumptions