Abstract: Convolutional layers (CLs) are ubiquitous in contemporary deep neural network (DNN) models, commonly used for automatic feature extraction. A CL performs cross-correlation between the input ...

Applying convolutional neural networks to a large number of EEG signal samples is computationally expensive because the computational complexity is linearly proportional to the number of dimensions of ...

Even though human experience unfolds continuously in time, it is not strictly linear; instead, it entails cascading processes building hierarchical cognitive structures. For instance, during speech ...

Abstract: Electromagnetic time reversal (EMTR) is drawing increasing interest in short-circuit fault location. In this article, we investigate the classic EMTR fault location methods and find that it ...

Steady state visually evoked potentials (SSVEPs) based early glaucoma diagnosis requires effective data processing (e.g., deep learning) to provide accurate stimulation frequency recognition. Thus, we ...

Audio equalization is the process of adjusting the balance between frequency components within an audio signal. The purpose of equalization is to make an audio signal sound better, more clear, and ...

Signals that carry information play a central role in technology and engineering — signals ranging from sound and images to sensors, radar, communication, MRI, ultrasound, touch-screens, GPS, and ...

Did you know that you can use LTspice to do Digital Signal Processing (DSP)? Actually, I should say it is useful for validating the operation of a signal-processing algorithm under development. This ...