The use of piezoelectric sensor arrays to measure contact forces has been extensively
studied in connection to robotics. In this research, Polyvinylidene Fluoride (PVDF) has been …

In linear algebra, Singular Value Decomposition (SVD) refers to factorization process of real
or complex matrices that has many applications in engineering, including signal processing …

This paper proposes SSketch, a novel automated computing framework for FPGA-based
online analysis of big data with dense (non-sparse) correlation matrices. SSketch targets …

As a useful tool for dimensionality reduction, Singular Value Decomposition (SVD) plays an
increasingly significant role in many scientific and engineering applications. The high …

Principal Component Analysis (PCA) is a widely used method for dimensionality reduction in
different application areas, including microwave imaging where the size of input data is …

Singular value decomposition (SVD) is a fundamental computational kernel and tool wildly
used in data analytics such as least squares regression, principle components analysis …

In recent years, tensor computation has become a promising tool for solving big data
analysis, machine learning, medical image, and EDA problems. To ease the memory and …

We propose SSketch, a novel automated framework for efficient analysis of dynamic big data
with dense (non-sparse) correlation matrices on reconfigurable platforms. SSketch targets …

In this paper we present a CORDIC based FPGA implementation of Singular Value
Decomposition for real time tactile information processing. The design is implemented to …

This paper presents a fast and generic hardware architecture for channel matrix singular
value decomposition (SVD) in massive multiple-input multiple-output (MIMO) system. A fixed …