The 2D signal is then processed using 2D convolution. This reduces the memory footprint and the hardware requirements for processing the signal. We evaluate the performance of the proposed technique ...

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Keywords: biomedical signals, non-stationary signal to 2D image representation, 2D convolution neural network (2D CNN), Bresenham’s line algorithm, electroencephalogram (EEG) Citation: Patel SA and ...

recognizing emotions from speech signals is one of the active research fields in the area of human information processing as well as man-machine interaction. Different persons have different emotions ...

2D image convolution is ubiquitous in image processing and computer vision problems such as feature extraction. Exploiting parallelism is a common strategy for accelerating convolution. Parallel ...

Convolution in frequency domain can help you understand how a filter or a system affects the frequency components of a signal. If you plot the magnitude and phase of the Fourier transform of the ...