Results 281 to 290 of about 1,240,549 (346)

Selecting Criteria for Optimizing Parameters of ADC for Digital Signal Processing

2019 International Russian Automation Conference (RusAutoCon), 2019
The paper presents the modern criteria analysis for the synthesizing the small-bit ADC and the evaluation of the ADC quantization noise dispersion with linear or nonlinear quantization step when choosing optimal values for thresholds and quantizer levels.
V. I. Akimov, A. V. Polukazakov, N. Sitnikov   +2 more
semanticscholar   +1 more source

Distributed Quantization-Aware RLS Learning With Bias Compensation and Coarsely Quantized Signals

IEEE Transactions on Signal Processing, 2022
In this work, we present an energy-efficient distributed learning framework using coarsely quantized signals for Internet of Things (IoT) networks. In particular, we develop a distributed quantization-aware recursive least-squares (DQA-RLS) algorithm ...
A. Danaee, R. Lamare, V. Nascimento
semanticscholar   +1 more source

Hybrid Optical Phase Quantization for All-optical Signal Processing

Asia Communications and Photonics Conference 2015, 2015
Recent progress in all-optical signal processing based on the novel hybrid optical phase squeezer (HOPS) is presented. After reviewing the principle, we experimentally demonstrate various configurations of HOPS to phase-regenerate BPSK signal and QPSK signal.
Takayuki Kurosu, Hung Nguyen Tan, Karen Solis-Trapala, Shu Namiki   +3 more
openaire   +1 more source

Multirate Digital Signal Processing and Noise Suppression for Dual Active Bridge DC–DC Converters in a Power Electronic Traction Transformer

IEEE transactions on power electronics, 2018
Power electronic traction transformer (PETT) is a single-phase ac–dc conversional system, which is made up of a cascaded H-bridge converter and output-parallel dc–dc converters, such as dual active bridge dc–dc (DAB) converters.
Jingxi Yang, Jianqiang Liu, Jiepin Zhang, Nan Zhao, Yang Wang, T. Zheng   +5 more
semanticscholar   +1 more source

A Self-Organizing Algorithm for Vector Quantizer Design Applied to Signal Processing

International Journal of Neural Systems, 1999
Vector quantization plays an important role in many signal processing problems, such as speech/speaker recognition and signal compression. This paper presents an unsupervised algorithm for vector quantizer design. Although the proposed method is inspired in Kohonen learning, it does not incorporate the classical definition of topological neighborhood ...
F, Madeiro, R M, Vilar, J M, Fechine, B G, Neto   +3 more
openaire   +2 more sources

Signal processing by random reference quantizing

Signal Processing, 1979
Abstract This paper deals with the propertie of Quantizer transfer characteristic smoothing when a quantizer with random parameters is used instead of a classical deterministic quantizer (Random Quantization). The author establishes a mathematical expression of the smoothing of the transfer characteristic, for any order moment of the quantized ...
openaire   +1 more source

A Signal-Dependent Error Arising in Digitally Processed Images Due to Quantization

IEEE Transactions on Computers, 1972
A troublesome error has been found in digital data which represents an image renormalized by a computer. The error, which takes the form of anomalous patterns in the switching sequence of certain bits, contributes unnecessary, signal-dependent noise to the-data.
Carter, William H., Brown, V. Dean
openaire   +1 more source

Ternary Spike-based Neuromorphic Signal Processing System

Neural Networks
Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fields, resulting in significant enhancements in performance.
Shuai Wang, Dehao Zhang, A. Belatreche, Yichen Xiao, Hongyu Qing, Wenjie Wei, Malu Zhang, Yang Yang   +7 more
semanticscholar   +1 more source

Detection and Localization of One-Bit Signal in Multiple Distributed Subarray Systems

IEEE Transactions on Signal Processing, 2023
A multiple distributed subarray (MDS) system usually transmits the raw data to the fusion center (FC), where the target detection and localization can be processed.
Lihua Ni, Di Zhang, Yimao Sun, Ning Liu, Jing Liang, Q. Wan   +5 more
semanticscholar   +1 more source

Coefficient quantization effects in digital signal processing

ICASSP '77. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A statistical analysis of the effects of coefficient quantization, which takes into account the quantization of the multiplication result, is presented. It is shown that the logarithm of the coefficient quantization noise power is proportional to the coefficient word length.
openaire   +1 more source