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Nilanka Rajapaksha

Researcher at University of Akron

Publications -  16
Citations -  183

Nilanka Rajapaksha is an academic researcher from University of Akron. The author has contributed to research in topics: Field-programmable gate array & Very-large-scale integration. The author has an hindex of 6, co-authored 16 publications receiving 162 citations.

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Low-Power VLSI Architectures for DCT\/DWT: Precision vs Approximation for HD Video, Biomedical, and Smart Antenna Applications

TL;DR: The methods discussed in the paper can be used in the design of emerging low-power digital systems having lowest complexity at the cost of a loss in accuracy?the optimal trade-off of computational accuracy for lowest possible complexity and power.
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Multiplier-free DCT approximations for RF multi-beam digital aperture-array space imaging and directional sensing

TL;DR: A novel DCT approximation having zero multiplicative complexity is shown to be better for multi-beamforming AAs when compared to BAS-2008 and CB-2011, implying the fastest DCT approximations using reconfigured logic devices in the literature.
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2D space---time wave-digital multi-fan filter banks for signals consisting of multiple plane waves

TL;DR: Close-form 2D wave-digital filter design equations and corresponding hardware architectures are proposed for realizing M independent fan-shaped passbands having independently steerable directionality and selectivity and are shown to be suitable for real-time sensor-array beamforming applications using custom VLSI circuits.
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DFT Computation Using Gauss-Eisenstein Basis: FFT Algorithms and VLSI Architectures

TL;DR: Three FRS architectures based on the Dempster-McLeod representation, expansion factor, and addition aware quantization are proposed, which are compared with competing algorithms in terms of arithmetic complexity.
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A Single-Channel Architecture for Algebraic Integer-Based 8 $\,\times\,$ 8 2-D DCT Computation

TL;DR: An area efficient row-parallel architecture is proposed for the real-time implementation of bivariate algebraic integer (AI) encoded 2-D discrete cosine transform (DCT) for image and video processing.