Abstract: Automatic modulation classification (AMC) is vital in cognitive communication systems. Existing AMC methods are mainly designed for Gaussian noise channels, but research shows that ...
Abstract: Deep-learning is widely used in modulation classification to reduce labor and improve the efficiency. Graph convolutional network (GCN) is a type of feature extraction network for graph data ...
Breast tumor segmentation in ultrasound imaging is critical for early diagnosis and treatment planning. However, precise breast tumor segmentation still remains challenging, mainly due to varying ...
Pulse density modulation (PDM) is a compact digital audio format used in devices like MEMS microphones and embedded systems. This compact primer eases you into the essentials of PDM audio. Let’s begin ...
Doing more with less in electronics often means improving power density. One of the new areas garnering attention involves applying a variety of advanced modulation techniques, including PWM and space ...
van Vliet and colleagues show a useful correlation between internal states of a convolutional neural network (CNN) trained on visual word stimuli with three specific components of evoked MEG ...
This article introduces a novel method for emulating piano sounds. We propose to exploit the sine, transient, and noise decomposition to design a differentiable spectral modeling synthesizer ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results