Two’s complement signal representation is widely used in the implementation of arithmetic operations. However, it is well-known that its sign-extension can cause undesirable signal transitions in the MSBs of a data-path circuit. We propose a novel technique to reduce the signal transitions due to sign-extension while retaining the simplicity of the two’s complement arithmetic operations. The ke...

Efficient speech signal representations are prerequisite for efficient speech processing algorithms. The Vandermonde transform is a recently introduced time-frequency transform which provides a sparse and uncorrelated speech signal representation. In contrast, the Fourier transform only decorrelates the signal approximately. To achieve complete decorrelation, the Vandermonde transform is signal...

Due to the inevitable acquisition system noise and strong background noise, it is often difficult detect features of weak signals. To solve this problem, sparse representation can effectively extract useful information according characteristics However, less effective against non-Gaussian white noise. Therefore, a novel SRSVD method combining singular value decomposition proposed further improv...

An important problem in signal analysis is to define a general purpose signal representation which is well adapted for developing pattern recognition algorithms. In this paper we will show that such a representation can be defined from the position of the zero-crossings and the local energy values of a dyadic wavelet decomposition. This representation is experimentally complete and admits a sim...

In recent years, the physiological measurement based on remote photoplethysmography has attracted wide attention, especially since epidemic of COVID-19. Many researchers paid great efforts to improve robustness illumination and motion variation. Most existing methods divided ROIs into many sub-regions extracted heart rate separately, while ignoring fact that rates from different are consistent....