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A Voice Inversion System To Estimate Vocal Fold Properties From Voice Acoustics

Prof. Zhang in the Department of Head and Neck Surgery has developed a voice inversion system that assesses the physiological state underlying voice production. The system can be used to diagnose vocal fold disorders as well as determine the emotional state of a speaker.

Absorptive Microwave Bandpass Filters

Researchers at the University of California, Davis have developed absorptive bandpass filters that enable improved passband flatness and good impedance matching both in-band and out-of-band.

A Fully Integrated Stretchable Sensor Arrays for Wearable Sign Language Translation To Voice

UCLA researchers in the Department of Bioengineering have developed a novel machine learning assisted wearable sensor system for the direct translation of sign language into voice with high performance.

New And Integrated Method For Continuous Auditory Brain Stimulation

Various examples of delivering continuous auditory stimulation of various kinds (sometimes referred to by the term “entrainment”) have been proposed to modulate brainwaves for therapeutic effect. Current methods of delivering continuous auditory stimulation typically present noises (in the form of clicks, tones, pulses) embedded in music. By modulating the user’s existing audial environment to embed continuous auditory sound stimulation, this technology creates a more tolerable and user-friendly experience that enables prolonged therapeutic stimulation for such neurodegenerative disorders as Alzheimer’s, Parkinson’s and Chronic Traumatic Encephalopathy (CTE).

Vibration Sensing and Long-Distance Sounding with THz Waves

UCLA researchers in the Department of Electrical and Computer Engineering have developed a terahertz (THz) detector that utilizes the micro-Doppler effect to detect vibrations and long-distance sounds.

Decision Making Spike Time Dependent Plasticity (STDP) Based Neuronal Network Learning

Biologically inspired neural networks are capable of performing sophisticated information processing. Information processing by the brain is multilayered and involves many sequential steps before sensory information can be interpreted and translated into a behavior or action. What makes this cascade powerful is its ability to learn and respond to an ever changing environment based on patterns. Eventually, information gathered from the senses may reach decision centers (such as lateral intra parietal cortex) that govern behavior and are under the influence of reward signals. While a great deal of research has gone into understanding mechanisms of learning at the cellular level, there is still much to discover regarding how learning at the cellular level gives rise to learning on the level of animal behavior. One of the most promising mechanisms of synaptic change for learning is spike time dependent plasticity ("STDP").

Self-Adaptive Architected Materials for Selective Damping of High Amplitude Sounds

Researchers in the UCLA Department of Mechanical and Aerospace Engineering and Department of Electrical and Computer Engineering have developed a responsive hearing protection system that uses self-adaptive architected materials that selectively dampens high amplitude, damaging sounds.

Deep Learning Network and Compression Framework over Limited Bandwidth Network Links

Researchers at the University of California, Davis have developed a technology that enables the quantization of discrete wavelet transformed coefficients to reduce bandwidth for cloud-based storage applications. 

Energy Efficient and Scalable Reconfigurable All-to-All Switching Architecture

Researchers at the University of California, Davis have developed a hierarchical optical switch architecture that is low latency and energy efficient.

Multi-Wavelength, Laser Array

Researchers at the University of California, Davis have developed a multi-wavelength, laser array that generates more precise wavelengths than current technologies. The array also delivers narrow linewidths and can operate athermally.

Higher-Speed and More Energy-Efficient Signal Processing Platform for Neural Networks

Researchers at the University of California, Davis have developed a nanophotonic-based platform for signal processing and optical computing in algorithm-based neural networks that is faster and more energy-efficient than current technologies.

A Method For Universal Two-Tap Feed-Forward Equalization Using A Differential Element

A fully tunable feed-forward equalizer with simplified addition and inversion operations that use a single differential element.

Quality Factor Enhancement For Highly-Selective Miniaturized Bandpass Filters

UCLA researchers in the Department of Electrical and Computer Engineering have developed narrowband and high-selective filters with zero-insertion loss.

Method Of Creating Scalable Broadband And Tunable Light Emitter At The Nanoscale Using Layered Black Phosphorus

UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel method to create a room temperature stable broadband tunable light emitter at the nanoscale.

Dicom/Pacs Compression Techniques

Researchers led by Xiao Hu from the Department of Surgery at UCLA have created a novel and convenient way to compress and query medical images from a PACS system.

Privacy Preserving Stream Analytics

UCLA researchers in the Department of Computer Science have developed a new privacy preserving mechanism for stream analytics.

Field Effect Bipolar Transistor

Researchers at the University of California have developed a field effect bipolar transistor (FEBT) on a unilateral silicon substrate using CMOS/BiCMOS technology for use in switching and amplification of electric signals and as a 1-transistor memory cell for storing information in a suitable circuit.

Nonlinearity Factorization for Up-Conversion Mixer Linearity Analysis

Researchers at the University of California, Davis have developed a nonlinearity factorization scheme/method to fully characterize the time-varying behavior of switching stages with low intermediate frequency (IF).

Passive Coupling Balance Scheme for Long Traveling Complex Differential Signals

Researchers at the University of California, Davis have developed a passive coupling balance technique to suppress signal mismatches for long traveling N-pair complex differential signals.

SpeakQL: Towards Speech-driven Multi-Modal Querying

Automatic speech recognition (ASR) systems currently in use work well for routine tasks such as posing a question to SIRI (Apple) or Alexa (Amazon), but do not interface with more complex datasets. Complex datasets take into account when the user considers a speech-driven system to query structured data, but these require new approaches. Some of these approaches have used new querying modalities such as visual, touch-based and natural language interfaces (NLIs) whereby user commands are translated into the Structured Query Language (SQL). Unfortunately these new proposals are not suitable for complex datasets.

Vertical Cavity Surface-Emitting Lasers with Continuous Wave Operation

An m-plane VCSEL with an active region that has thick quantum wells and operation in continuous wave.

A Digital Polar and a ZVS Contour Based Hybrid Power Amplifier

Researchers in the UCLA Department of Electrical Engineering have created a hybrid digital polar and zero switching voltage (ZVS) contour power amplifier, offering higher efficiency for up to 36 dB peak-to-average ratio.

Energy-Efficient All-Optical Nanophotonic Computing

Researchers at the University of California, Davis, have developed a new computing and signal processing platform based on nanophotonics and nanoelectronics to decrease power consumption and improve overall computing speed with all-optical inputs and outputs.

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