Radio World

A Class on Predicting FM Radio Signals

In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...

Volcanoes Send Tiny Warning Signals Before Eruptions. These Scientists Are Decoding Them

The team behind "Jerk," a novel tool that predicted eruptions with 92% accuracy for a French volcano, discusses its work and ...
eLife

Modality-agnostic decoding of vision and language from fMRI

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Live Science

Largest crowd-sourced hunt for alien intelligence reveals 12 billion 'signals of interest' in collapsed Arecibo Observatory data

A crowd-sourced search for alien intelligence called SETI@Home is in its final stages, analyzing 100 'signals of interest' with the world's largest radio telescope. When you purchase through links on ...
IEEE

MTSNet: Convolution-Based Transformer Network With Multi-Scale Temporal-Spectral Feature Fusion for SSVEP Signal Decoding

Abstract: Improving the decoding performance of steady-state visual evoked (SSVEP) signals is crucial for the practical application of SSVEP-based brain-computer interface (BCI) systems. Although ...
Scientific Research Publishing

Wen, T. and Zhang, Z. (2018) Deep Convolution Neural Network and Autoencoders-Based Unsupervised Feature Learning of EEG Signals. IEEE Access, 6, 25399-25410.

ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...
GitHub

convolution_neural_network.py

self, conv1_get, size_p1, bp_num1, bp_num2, bp_num3, rate_w=0.2, rate_t=0.2 :param conv1_get: [a,c,d], size, number, step of convolution kernel :param size_p1 ...