Results 11 to 20 of about 541,388 (266)
Signal Quantization Effects on Acquisition Process of GPS Receiver: The Analysis and Simulation
2008 Congress on Image and Signal Processing, 2008 Signal quantization levels can have significant impact on the performance of a GPS receiver, especially in the present of the interference. In this paper, signal quantization model for estimating interference suppression of the correlator output and evaluating the performance of GPS receiver is presented.
Chuanrun Zhai, Zhe He, Xingqun Zhan
openaire +4 more sources
ICTACT Journal on Microelectronics, 2016 An accurate design of low power Voltage Controlled Oscillator (VCO) enabled quantizer in Continuous Time Sigma Delta ADC in 180nm CMOS technology using Tanner EDA tools is done. The proposed architecture consists of the loop filter, VCO quantizer and the DAC in the feedback side of model.
Anil Kumar Sahu, Anikta Khurana
+6 more sources
Enhanced Multi-Level Phase Quantizer for the Optical Processing of M-PSK Signals
Journal of Lightwave Technology, 2016 This paper presents a novel multi-level phase quantizer with the potential of almost ideal step like transfer function. Its operation relies on the proper combination of phase sensitive amplification in highly nonlinear fibers and amplitude limitation offered by injection locked lasers.
Bogris, A., Pikasis, E.
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Optimization of Quantized Analog Signal Processing Using Genetic Algorithms and μ-Law [PDF]
IEEE Open Journal of Circuits and Systems, 2022 Qingnan Yu +2 more
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Optimal Controller Synthesis and Dynamic Quantizer Switching for Linear-Quadratic-Gaussian Systems [PDF]
IEEE Transactions on Automatic Control, 2021, 2020 In networked control systems, often the sensory signals are quantized before being transmitted to the controller. Consequently, performance is affected by the coarseness of this quantization process. Modern communication technologies allow users to obtain resolution-varying quantized measurements based on the prices paid.
arxiv +1 more source
Quantization Errors of fGn and fBm Signals [PDF]
Zhiheng Li, Yudong Chen, Li Li*, Yi Zhang, "Quantization errors of
uniformly quantized fGn and fBm signals," IEEE Signal Processing Letters,
vol. 16, no. 12, pp. 1059-1062, 2009., 2009 In this Letter, we show that under the assumption of high resolution, the quantization errors of fGn and fBm signals with uniform quantizer can be treated as uncorrelated white noises.
arxiv +1 more source
A note on the trade-off between sampling and quantization in signal processing
Journal of Complexity, 1987 AbstractWe discuss the trade-off between sampling and quantization in signal processing for the purpose of minimizing the error of the reconstructed signal subject to the constraint that the digitized signal fits in a given amount of memory. For signals with different regularities, we estimate the intrinsic errors from finite sampling and quantization,
Grzegorz W. Wasilkowski +2 more
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Quantization optimized with respect to the Haar basis [PDF]
arXiv, 2021 We propose a method of data quantization of finite discrete-time signals which optimizes the error estimate of low frequency Haar coefficients. We also discuss the error/noise bounds of this quantization in the Fourier space. Our result shows one can quantize any discrete-time analog signal with high precision at low frequencies.
arxiv
Hardware Implementation of Task-based Quantization in Multi-user Signal Recovery [PDF]
arXiv, 2023 Quantization plays a critical role in digital signal processing systems, allowing the representation of continuous amplitude signals with a finite number of bits. However, accurately representing signals requires a large number of quantization bits, which causes severe cost, power consumption, and memory burden. A promising way to address this issue is
arxiv
Dynamic Signal Measurements Based on Quantized Data [PDF]
IEEE Transactions on Instrumentation and Measurement, Year: 2017,
Volume: 66, Issue: 2 Pages: 223 - 233, 2018 The estimation of the parameters of a dynamic signal, such as a sine wave, based on quantized data is customarily performed using the least-square estimator (LSE), such as the sine fit. However, the characteristics of the experiments and the measurement setup hardly satisfy the requirements ensuring the LSE to be optimal in the minimum mean-square ...
arxiv +1 more source