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Search Results - advanced+computing+methods
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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
Method of Proficient Typing Using a Limited Number of Classes (Case No. 2024-063)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel software algorithm to rapidly predict text using small keyboards for various applications, including mobile computing, gaming, and human-computer interactions. Background: Advancements in mobile computing have drastically changed everyday life...
Published: 2/14/2025
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Inventor(s):
Jonathan Kao
,
Shreyas Kaasyap
,
John Zhou
,
Johannes Lee
,
Nima Hadidi
Keywords(s):
Advanced Computing / AI
,
advanced computing methods
,
all-optical diffractive computing
,
Artificial Neural Network
,
Artificial Neural Network Artificial Neuron
,
assistive communication
,
background radiation
,
Bandwidth (Computing)
,
Brain computer interface
,
brain machine interface
,
Classroom management software
,
Cloud Computing
,
composite scintillators
,
Database management/data entry
,
deep physical neural network
,
design software
,
edge computing
,
fast scintillators
,
gamma spectroscopy
,
graph neural network
,
HCI (Human Computer Interaction)
,
high-Z organometallics
,
Human/Brain computer interfaces (BCI/HCI)
,
human-centered computing
,
material characterization
,
Medical science computing
,
mobile computing
,
modular robotic system
,
nanocomposite scintillators
,
neural network
,
neural networks
,
neutrino detection
,
Optical computing
,
positron emission tomography (PET)
,
predictive text
,
primary school software
,
radiation detection
,
recurrent neural networks
,
Robotics
,
robotics control
,
scintillators
,
second harmonic generation
,
secondary school software
,
self-sustaining computing
,
soft robotics
,
Software
,
Software & Algorithms
,
Software Development Tools
,
Software-enabled learning
,
Spatial computing
,
Stochastic Computing (SC)
,
T6 keyboard
,
T9 keyboard
,
visual computing
,
wafer-scale computing
Category(s):
Software & Algorithms
,
Software & Algorithms > Artificial Intelligence & Machine Learning
,
Software & Algorithms > Communication & Networking
Polyqubit Encoding for Quantum Information Processing (Case No. 2023-006)
Summary: UCLA researchers in the Physics and Astronomy Department have developed a quantum information processing method that encodes multiple qubits within single atoms in trapped atom quantum processors, enabling efficient qubit manipulation for enhanced computational capacity. Background: Quantum computing is an emerging technology with immense...
Published: 3/20/2025
|
Inventor(s):
Wesley Campbell
,
Eric Hudson
Keywords(s):
advanced computing methods
,
atomic processor
,
Electronics & Semiconductors
,
information storage
,
polyqubit
,
polyqubit encoding
,
polyqubit processing
,
Quantum Computer
,
quantum error correction (QEC)
,
quantum processing
,
quantum processor
,
qubit-host-limited (QHL)
,
system control resources
,
trapped ion quantum processor
Category(s):
Electrical
,
Electrical > Quantum Computing