Recent speech-aware large language models (Speech-LLMs) rely on a pre-trained speech encoder to convert audio into semantic-rich representations consumable by LLM. In this work, instead, we explore: ...

Abstract: We investigate the performance of a discrete-time all-analog-processing joint source-channel coding system for the transmission of memoryless sources over average power constrained AWGN ...

Abstract: We study the linear quadratic Gaussian (LQG) control problem, in which the controller's observation of the system state is insufficient to attain a desired quadratic control cost. To achieve ...

A roundup of new products at Automate 2026, spanning integrated motion platforms, edge computing, adaptive robotics and ...

The ATOM DX encoder is built on the optical system platform of the market-proven ATOM ™ encoder. It integrates Renishaw's ...

Or, if you prefer, you can use the "Download Zip" button available through the main repository page. Downloading the project as a .ZIP file will keep the size of the ...

A study published in Nature Physics provides new molecular-level evidence from simulations that liquid water is not a single ...

The next wave of robotics depends on unifying code and hardware—embedding AI directly into the deterministic systems that ...

Large-scale pre-trained language models have been shown to be helpful in improving the naturalness of text-to-speech (TTS) models by enabling them to produce more naturalistic prosodic patterns.

It offers rotary servo motors, direct drive motors, linear motors/linear sliders, machine controllers, positioning sensor encoders, and servo amplifiers for use in industrial robots, semiconductor ...