Search Results - matrix+multiplication

1 Results

Sort By:

Event-Driven Integrate and Fire (EIF) Neuron Circuit for Neuromorphic Computing System (Case No. 2024-275)

Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed an energy efficient neuromorphic computing architecture. Background: Widespread growth in demand for artificial intelligence systems has highlighted limitations in current central processing unit (CPU) designs, particularly in terms of energy efficiency...

Published: 3/4/2025 | Inventor(s): Mau-Chung Chang, Chao Jen Tien, Yong Hei

Keywords(s): Advanced Computing / AI, advanced computing methods, AI hardware, analog computing, Artifical Intelligence (Machine Learning, Data Mining), artificial electromagnetic materials, Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial intelligence-generated content, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial presenting cells, artificial-intelligent materials, Cloud Computing, computational efficiency, computational imaging, compute-in-memory, Computer Aided Learning, Computer Architecture, Computer Monitor, Computer Vision, CPU design, deep neural networks (DNN), Energy Density, Energy Efficiency, event-driven processing, generative artificial intelligence, latency encoding, low latency computing, low-power architecture, matrix multiplication, Medical artificial intelligence (AI), Neuromorphic computing, offline learning, online learning, spike neural networks (SNN), Supercomputer

Category(s): Electrical, Electrical > Signal Processing, Electrical > Electronics & Semiconductors, Electrical > Computing Hardware, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning