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Journal articles on the topic 'High-Resolution quantization'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Korten, Pim, Jesper Jensen, and Richard Heusdens. "High-Resolution Spherical Quantization of Sinusoidal Parameters." IEEE Transactions on Audio, Speech and Language Processing 15, no. 3 (2007): 966–81. http://dx.doi.org/10.1109/tasl.2006.885929.

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2

Viswanathan, H., and R. Zamir. "On the whiteness of high-resolution quantization errors." IEEE Transactions on Information Theory 47, no. 5 (2001): 2029–38. http://dx.doi.org/10.1109/18.930935.

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3

Kreitmeier, Wolfgang, and Tamás Linder. "High-Resolution Scalar Quantization With Rényi Entropy Constraint." IEEE Transactions on Information Theory 57, no. 10 (2011): 6837–59. http://dx.doi.org/10.1109/tit.2011.2165809.

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4

Goldberg, Naftaly. "Colour image quantization for high resolution graphics display." Image and Vision Computing 9, no. 5 (1991): 303–12. http://dx.doi.org/10.1016/0262-8856(91)90035-n.

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5

Lookabaugh, T. D., and R. M. Gray. "High-resolution quantization theory and the vector quantizer advantage." IEEE Transactions on Information Theory 35, no. 5 (1989): 1020–33. http://dx.doi.org/10.1109/18.42217.

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6

Aurzada, Frank, Steffen Dereich, Michael Scheutzow, and Christian Vormoor. "High resolution quantization and entropy coding of jump processes." Journal of Complexity 25, no. 2 (2009): 163–87. http://dx.doi.org/10.1016/j.jco.2008.10.002.

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7

AL-Qaysi, Hayder Khaleel, Tahreer Mahmood, and Khalid Awaad Humood. "Evaluation of different quantization resolution levels on the BER performance of massive MIMO systems under different operating scenarios." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 3 (2021): 1493. http://dx.doi.org/10.11591/ijeecs.v23.i3.pp1493-1500.

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The massive MIMO system is one of the main technologies in the fifth generation (5G) of telecommunication systems, also recognized as a highly large-scale system. Constantly in massive MIMO systems, the base station (BS) is provided with a large number of antennas, and this large number of antennas need high-quantization resolution levels analog-to-digital converters (ADCs). In this situation, there will be more power consumption and hardware costs. This paper presents the simulation performance of a suggested method to investigate and analyze the effects of different quantization resolution l

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AL-Qaysi, Hayder Khaleel, Tahreer Mahmood, and Khalid Awaad Humood. "Evaluation of different quantization resolution levels on the BER performance of massive MIMO systems under different operating scenarios." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 3 (2021): 1493–500. https://doi.org/10.11591/ijeecs.v23.i3.pp1493-1500.

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The massive MIMO system is one of the main technologies in the fifth generation (5G) of telecommunication systems, also recognized as a highly large-scale system. Constantly in massive MIMO systems, the base station (BS) is provided with a large number of antennas, and this large number of antennas need high-quantization resolution levels analog-to-digital converters (ADCs). In this situation, there will be more power consumption and hardware costs. This paper presents the simulation performance of a suggested method to investigate and analyze the effects of different quantization resolution l

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9

Jiang, Jun, Lianping Guo, Kuojun Yang, and Huiqing Pan. "Information Entropy- and Average-Based High-Resolution Digital Storage Oscilloscope." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/947052.

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Vertical resolution is an essential indicator of digital storage oscilloscope (DSO) and the key to improving resolution is to increase digitalizing bits and lower noise. Averaging is a typical method to improve signal to noise ratio (SNR) and the effective number of bits (ENOB). The existing averaging algorithm is apt to be restricted by the repetitiveness of signal and be influenced by gross error in quantization, and therefore its effect on restricting noise and improving resolution is limited. An information entropy-based data fusion and average-based decimation filtering algorithm, proceed

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10

Zhang, Wence, Jing Xia, and Xu Bao. "Massive MIMO Systems with Low-Resolution ADCs: Achievable Rates and Allocation of Quantization Bits." Wireless Communications and Mobile Computing 2023 (February 17, 2023): 1–12. http://dx.doi.org/10.1155/2023/4012841.

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In massive multiple-input multiple-output (MIMO) systems, the large number of high-resolution analog-to-digital converters (ADCs) lead to high hardware cost and power consumption. In this work, the uplink achievable rates of massive MIMO systems with low-resolution ADCs are studied with consideration of both “Uniform-ADC” that uses ADCs with the same number of quantization bits and “Mixed-ADC” that allows the use of ADCs with different resolutions. By leveraging an additive quantization noise model (AQNM), the asymptotic achievable rates are obtained for maximum ratio combining (MRC), zero-for

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11

Koch, Tobias, and Gonzalo Vazquez-Vilar. "A Rigorous Approach to High-Resolution Entropy-Constrained Vector Quantization." IEEE Transactions on Information Theory 64, no. 4 (2018): 2609–25. http://dx.doi.org/10.1109/tit.2018.2803064.

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12

Bach, Volker, and Ruedi Seiler. "Analysis of Optimal High Resolution and Fixed Rate Scalar Quantization." IEEE Transactions on Information Theory 55, no. 4 (2009): 1683–91. http://dx.doi.org/10.1109/tit.2009.2013020.

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13

Misra, Vinith, Vivek K. Goyal, and Lav R. Varshney. "Distributed Scalar Quantization for Computing: High-Resolution Analysis and Extensions." IEEE Transactions on Information Theory 57, no. 8 (2011): 5298–325. http://dx.doi.org/10.1109/tit.2011.2158882.

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14

Dereich, S., and C. Vormoor. "The High Resolution Vector Quantization Problem with Orlicz Norm Distortion." Journal of Theoretical Probability 24, no. 2 (2010): 517–44. http://dx.doi.org/10.1007/s10959-010-0327-2.

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15

Dereich, Steffen, and Michael Scheutzow. "High Resolution Quantization and Entropy Coding for Fractional Brownian Motion." Electronic Journal of Probability 11 (2006): 700–722. http://dx.doi.org/10.1214/ejp.v11-344.

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16

Tozer, Daniel J., and Paul S. Tofts. "Removing spikes caused by quantization noise from high-resolution histograms." Magnetic Resonance in Medicine 50, no. 3 (2003): 649–53. http://dx.doi.org/10.1002/mrm.10561.

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17

Lv, Zhongze, Ying Huang, Hu Guan, Jie Liu, Shuwu Zhang, and Yang Zheng. "Adaptive Video Watermarking against Scaling Attacks Based on Quantization Index Modulation." Electronics 10, no. 14 (2021): 1655. http://dx.doi.org/10.3390/electronics10141655.

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Video watermarking plays a vital role in protecting the video copyright. The quantization-based methods are widely used in the existing watermarking algorithms, owing to their low computational complexity and completely blind extraction. However, most of them work poorly in resisting scaling attacks, by which the quantization value may fall outside the original quantization interval. For addressing this issue, an adaptive quantization index modulation method is proposed. The property that is associated with the ratio of the DC coefficient before and after scaling the video resolution motivates

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18

Luschgy, Harald, and Gilles Pagès. "High-resolution product quantization for Gaussian processes under sup-norm distortion." Bernoulli 13, no. 3 (2007): 653–71. http://dx.doi.org/10.3150/07-bej6025.

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19

Kreitmeier, W. "Error bounds for high-resolution quantization with Rényi-α-entropy constraints". Acta Mathematica Hungarica 127, № 1-2 (2010): 34–51. http://dx.doi.org/10.1007/s10474-010-9079-9.

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20

Raza, Md Salim, Nahid Hasan, Sayed Tonmoy Ahamed, Kazi Ghulam Mostafa, and Mohammad Rabiul Alam. "Optimization of the Ratio of Sampling Rate to Quantization Level for the Reconstruction of Audio Signal." International Journal of Sensors, Wireless Communications and Control 9, no. 1 (2019): 111–23. http://dx.doi.org/10.2174/2210327908666180817103609.

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Background and Objective: In this research work, the basic digital communication system with frequency shift keying modulation technique has been implemented in MATLAB. Methods: The same sinusoidal signal in audio frequency range has been transmitted and reconstructed with the different number of quantization level and sampling rate, where sampling frequency has been taken according to the Nyquist theorem. It has been seen that reconstructed signal at low data rate has appeared with better resolution compared with the reconstructed signal at the high data rate. Results and Conclusion: In this

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21

Jun, Liu, Luo Zhongqiang, and Xiong Xingzhong. "Low-Complexity Synchronization Scheme with Low-Resolution ADCs." Information 9, no. 12 (2018): 313. http://dx.doi.org/10.3390/info9120313.

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An important function of next-generation (5G) and beyond mobile communication systems is aim to provide thousand-fold capacity growth and to support high-speed data transmission up to several megabits per second. However, the research community and industries have to face a dilemma of power consumption and hardware design to satisfy the increasing communication requirements. For the purpose of improving the system cost, power consumption, and implementation complexity, a novel scheme of symbol timing and frequency offset estimation with low-resolution analog-to-digital converters (ADCs) based

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22

Huang, Bormin, Alok Ahuja, and Hung-Lung Huang. "Optimal Compression of High Spectral Resolution Satellite Data via Adaptive Vector Quantization with Linear Prediction." Journal of Atmospheric and Oceanic Technology 25, no. 6 (2008): 1041–47. http://dx.doi.org/10.1175/2007jtecha917.1.

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Abstract Contemporary and future high spectral resolution sounders represent a significant technical advancement for environmental and meteorological prediction and monitoring. Given their large volume of spectral observations, the use of robust data compression techniques will be beneficial to data transmission and storage. In this paper, a novel adaptive vector quantization (VQ)-based linear prediction (AVQLP) method for lossless compression of high spectral resolution sounder data is proposed. The AVQLP method optimally adjusts the quantization codebook sizes to yield the maximum compressio

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23

Gao, Jian, Peng Ye, Hao Zeng, et al. "Theory of Quantization-Interleaving ADC and Its Application in High-Resolution Oscilloscope." IEEE Access 7 (2019): 156722–32. http://dx.doi.org/10.1109/access.2019.2949701.

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24

Puidokas, Vytenis, and Albinas J. Marcinkevičius. "High Resolution High Power Low Frequency Digital-to-Analog Converter." Solid State Phenomena 164 (June 2010): 133–38. http://dx.doi.org/10.4028/www.scientific.net/ssp.164.133.

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The architectural scheme of the designed Sigma-Delta DAC on the FPGA is considered. The place of the interpolator in Sigma-Delta DACs is briefly discussed. The summarized structure of the most common interpolators is presented. More applicable structures of interpolators were suggested and analyzed, providing the comparison with [1]. Having changed the structure of the incomplete interpolator and having optimized the stages, it was possible to improve the characteristic of amplitude frequency response with a smaller number of non-zero coefficients and much lower FPGA resources. The paper provi

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25

JIANG, MINGHU, and GEORGES GIELEN. "THE EFFECTS OF QUANTIZATION ON MULTI-LAYER FEEDFORWARD NEURAL NETWORKS." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 04 (2003): 637–61. http://dx.doi.org/10.1142/s0218001403002514.

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In this paper we investigate the combined effect of quantization and clipping on multi-layer feedforward neural networks (MLFNN). Statistical models are used to analyze the effects of quantization in a digital implementation. We analyze the performance degradation caused as a function of the number of fixed-point and floating-point quantization bits in the MLFNN. To analyze a true nonlinear neuron, we adopt the uniform and normal probability distributions, compare the training performances with and without weight clipping, and derive in detail the effect of the quantization error on forward an

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26

Wang, Ning, Jian-Wen Bao, Jin-Luen Lee, Fanthune Moeng, and Cliff Matsumoto. "Wavelet Compression Technique for High-Resolution Global Model Data on an Icosahedral Grid." Journal of Atmospheric and Oceanic Technology 32, no. 9 (2015): 1650–67. http://dx.doi.org/10.1175/jtech-d-14-00217.1.

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AbstractModern Earth modeling systems often use high-resolution unstructured grids to discretize their horizontal domains. One of the major challenges in working with these high-resolution models is to efficiently transmit and store large volumes of model data for operational forecasts and for modeling research.A newly developed compression technique is presented that significantly reduces the size of datasets produced by high-resolution global models that are discretized on an icosahedral grid. The compression technique is based on the wavelet transform together with a grid rearrangement algo

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27

Fernandez-Rodriguez, Jose David, Esteban José Palomo, Jose Jesus Benito-Picazo, Enrique Dominguez, Ezequiel López-Rubio, and Francisco Ortega-Zamorano. "A convolutional autoencoder and a neural gas model based on Bregman divergences for hierarchical color quantization." Neurocomputing 544 (May 11, 2024): 126288. https://doi.org/10.1016/j.neucom.2023.126288.

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Color quantization (CQ) is one of the most common and important procedures to be performed on digital images. In this paper, a new approach to hierarchical color quantization is described, presenting a novel neural network architecture integrated by a convolutional autoencoder and a Growing Hierarchical Bregman Neural Gas (GHBNG). GHBNG is a CQ algorithm that allows the compression of an image by choosing a reduced set of the most representative colors to generate a high-quality reproduction of the original image. In the technique proposed here, an autoencoder is used to translate the image in

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28

Wielgosz, Maciej, and Andrzej Skoczeń. "Using Neural Networks with data Quantization for time Series Analysis in LHC Superconducting Magnets." International Journal of Applied Mathematics and Computer Science 29, no. 3 (2019): 503–15. http://dx.doi.org/10.2478/amcs-2019-0037.

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Abstract The aim of this paper is to present a model based on the recurrent neural network (RNN) architecture, the long short-term memory (LSTM) in particular, for modeling the work parameters of Large Hadron Collider (LHC) super-conducting magnets. High-resolution data available in the post mortem database were used to train a set of models and compare their performance for various hyper-parameters such as input data quantization and the number of cells. A novel approach to signal level quantization allowed reducing the size of the model, simplifying the tuning of the magnet monitoring system

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29

Wang, Siye, Yeqin Huang, and Yong Yang. "Ergodic Rate and Outage Performance of Full-Duplex NOMA Relaying with Channel Estimation Errors and Low-Resolution ADCs." Applied Sciences 13, no. 12 (2023): 6950. http://dx.doi.org/10.3390/app13126950.

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In this paper, we analyze the performance of a full-duplex (FD) cooperative non-orthogonal multiple access (C-NOMA) relaying system with an amplify-and-forward (AF) protocol in the presence of loopback interference in FD transceivers. Particularly, by considering channel estimation errors and quantization noise in low-resolution analog-to-digital converters (ADCs), the accurate approximation expression for the ergodic rate and closed-form solution for the outage probability are derived, respectively. The validity of the theoretical results is verified by Monte Carlo simulations, which show tha

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30

Mielens, Jason D., Matthew R. Hoffman, Michelle R. Ciucci, Timothy M. McCulloch, and Jack J. Jiang. "Application of Classification Models to Pharyngeal High-Resolution Manometry." Journal of Speech, Language, and Hearing Research 55, no. 3 (2012): 892–902. http://dx.doi.org/10.1044/1092-4388(2011/11-0088).

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Purpose The authors present 3 methods of performing pattern recognition on spatiotemporal plots produced by pharyngeal high-resolution manometry (HRM). Method Classification models, including the artificial neural networks (ANNs) multilayer perceptron (MLP) and learning vector quantization (LVQ), as well as support vector machines (SVM), were evaluated for their ability to identify disordered swallowing. Data were collected from 12 control subjects and 13 subjects with swallowing disorders; for this experiment, these subjects swallowed 5-ml water boluses. Following extraction of relevant param

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31

Wang, Mingshen, Zhao Zhang, Feng Li, Ke Xu, Kang Miao, and Meng Wang. "Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity Clues." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 8 (2025): 7826–34. https://doi.org/10.1609/aaai.v39i8.32843.

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Dynamic quantization has attracted rising attention in image super-resolution (SR) as it expands the potential of heavy SR models onto mobile devices while preserving competitive performance. Most current methods explore layer-to-bit configuration upon varying local regions, adaptively allocating the bit to each layer and patch. Despite the benefits, they still fall short in the tradeoff of SR accuracy and quantization efficiency. Apart from this, adapting the quantization level for each layer individually can disturb the original inter-layer relationships, thus diminishing the representation

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Khramkin, Ivan A., Maxim A. Savinykh, and Stanislav V. Ponomarev. "ESTIMATION OF QUANTIZATION ERROR IN MEASUREMENT OF ROOT-MEAN-SQUARE VALUES OF SINE SIGNALS." Electrical and data processing facilities and systems 20, no. 2 (2024): 139–51. http://dx.doi.org/10.17122/1999-5458-2024-20-2-139-151.

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Relevance In modern electric power industry, digital measuring devices are often used, which are based on the use of analog-to-digital converters (ADCs). Manufacturers of such devices face the choice of an ADC, in particular, the choice of its key characteristic – the resolution. In the context of measuring devices, the share of the cost of the ADC is one of the main ones in the cost of the final device. At the same time, manufacturers often lay down the ADC with the largest number of resolution binary digits, while obtaining an unreasonably high margin in the number of bits. The issue of choo

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Tai, Ying, Yicong Liang, Xiaoming Liu, et al. "Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8893–900. http://dx.doi.org/10.1609/aaai.v33i01.33018893.

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In recent years, heatmap regression based models have shown their effectiveness in face alignment and pose estimation. However, Conventional Heatmap Regression (CHR) is not accurate nor stable when dealing with high-resolution facial videos, since it finds the maximum activated location in heatmaps which are generated from rounding coordinates, and thus leads to quantization errors when scaling back to the original high-resolution space. In this paper, we propose a Fractional Heatmap Regression (FHR) for high-resolution video-based face alignment. The proposed FHR can accurately estimate the f

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34

Nikolic, Jelena, and Zoran Peric. "Two approaches to design of forward adaptive piecewise uniform scalar quantizers." Facta universitatis - series: Electronics and Energetics 26, no. 1 (2013): 61–68. http://dx.doi.org/10.2298/fuee1301061n.

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In this paper, two forward adaptive piecewise uniform scalar quantizers are proposed for high-quality quantization of speech signals modeled by the Laplacian probability density function. In designing both forward adaptive piecewise uniform scalar quantizers an equidistant support region partition is assumed and a distribution of the number of reproduction levels per segments is optimized. The proposed models differ in the approach of determining the reproduction levels. In particular, one model defines the reproduction levels as the cell centroids and the other one as the cell midpoints. We s

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Liu, Jiafeng, Haoyang Shi, Siyuan Zhang, Yin Yang, Chongyang Ma, and Weiwei Xu. "Automatic quantization for physics-based simulation." ACM Transactions on Graphics 41, no. 4 (2022): 1–16. http://dx.doi.org/10.1145/3528223.3530154.

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Quantization has proven effective in high-resolution and large-scale simulations, which benefit from bit-level memory saving. However, identifying a quantization scheme that meets the requirement of both precision and memory efficiency requires trial and error. In this paper, we propose a novel framework to allow users to obtain a quantization scheme by simply specifying either an error bound or a memory compression rate. Based on the error propagation theory, our method takes advantage of auto-diff to estimate the contributions of each quantization operation to the total error. We formulate t

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36

Bellan, Diego. "On the Validity of the Noise Model of Quantization for the Frequency-Domain Amplitude Estimation of Low-Level Sine Waves." Metrology and Measurement Systems 22, no. 1 (2015): 89–100. http://dx.doi.org/10.1515/mms-2015-0004.

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Abstract This paper deals with the amplitude estimation in the frequency domain of low-level sine waves, i.e. sine waves spanning a small number of quantization steps of an analog-to-digital converter. This is a quite common condition for high-speed low-resolution converters. A digitized sine wave is transformed into the frequency domain through the discrete Fourier transform. The error in the amplitude estimate is treated as a random variable since the offset and the phase of the sine wave are usually unknown. Therefore, the estimate is characterized by its standard deviation. The proposed mo

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37

Zheng, Jun, Ethan R. Duni, and Bhaskar D. Rao. "Analysis of Multiple-Antenna Systems With Finite-Rate Feedback Using High-Resolution Quantization Theory." IEEE Transactions on Signal Processing 55, no. 4 (2007): 1461–76. http://dx.doi.org/10.1109/tsp.2006.889407.

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38

Martinez, Dominique, and Marc M. Van Hulle. "Generalized boundary adaptation rule for minimizing rth power law distortion in high resolution quantization." Neural Networks 8, no. 6 (1995): 891–900. http://dx.doi.org/10.1016/0893-6080(95)00032-u.

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39

Ramalho, Leonardo, Igor Freire, Chenguang Lu, Miguel Berg, and Aldebaro Klautau. "Improved LPC-Based Fronthaul Compression with High Rate Adaptation Resolution." IEEE Communications Letters PP, no. 99 (2018): 1. https://doi.org/10.1109/LCOMM.2018.2791407.

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This paper presents a fronthaul signal compression scheme based on linear prediction coding (LPC) adapted to orthogonal frequency division multiplexing (OFDM) signals. The proposed method is capable of providing fine tuning of the compression factor, which is an alternative to legacy compression methods that tune the compression factor by changing the discrete number of bits of the quantizer and, consequently, are only able to do so with coarse resolution.

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Raj, Raghu G., Maxine R. Fox, and Ram M. Narayanan. "Target Classification in Synthetic Aperture Radar Images Using Quantized Wavelet Scattering Networks." Sensors 21, no. 15 (2021): 4981. http://dx.doi.org/10.3390/s21154981.

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The need to classify targets and features in high-resolution imagery is of interest in applications such as detection of landmines in ground penetrating radar and tumors in medical ultrasound images. Convolutional neural networks (CNNs) trained using extensive datasets are being investigated recently. However, large CNNs and wavelet scattering networks (WSNs), which share similar properties, have extensive memory requirements and are not readily extendable to other datasets and architectures—and especially in the context of adaptive and online learning. In this paper, we quantitatively study s

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SINGH, VIPULA, NAVIN RAJPAL, and K. SRIKANTA MURTHY. "A NEURO-WAVELET MODEL USING FUZZY VECTOR QUANTIZATION FOR EFFICIENT IMAGE COMPRESSION." International Journal of Image and Graphics 09, no. 02 (2009): 299–320. http://dx.doi.org/10.1142/s0219467809003447.

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Images have large data quantity. For storage and transmission of images, high efficiency image compression methods are under wide attention. In this paper, we propose a neuro- wavelet based model for image compression, which combines the advantages of wavelet transform and neural network and uses fuzzy vector quantization on hidden layer coefficients. Images are decomposed using wavelet filters into a set of sub bands with different resolution corresponding to different frequency bands. Different quantization and coding schemes are used for different sub bands based on their statistical proper

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Martinez, P., M. Beaulieu, L. Abe, et al. "High contrast at small separation – III. Impact on the dark hole of MEMS deformable mirror control electronics." Monthly Notices of the Royal Astronomical Society 532, no. 2 (2024): 2892–904. http://dx.doi.org/10.1093/mnras/stae1677.

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ABSTRACT The creation of a dark hole (DH) region in the science image for exoplanet direct detection depends on deformable mirrors (DMs), where the imperfect control of DM limits the achievable contrast. The mirror surface height resolution is set by the DM drive electronics, and the quantization errors in DM impact the contrast in the DH. Consequently, determining the optimal voltage value for the flattening map of DM is essential, as it involves balancing dynamic and accuracy considerations. We conduct a numerical study to examine the impact of these parameters on microelectromechanical DM w

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NAGASHIMA, Tomotaka, Takema SATOH, Petre CATALIN, Kazuyoshi ITOH, and Tsuyoshi KONISHI. "Parallel Use of Dispersion Devices for Resolution Improvement of Optical Quantization at High Sampling Rate." IEICE Transactions on Electronics E97.C, no. 7 (2014): 787–94. http://dx.doi.org/10.1587/transele.e97.c.787.

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44

Zhong, Yi, Jin Shao, Changyou Men та Nan Sun. "A Closed-Loop VCO-based 1-1 SMASH CT ΔΣ ADC Architecture". Journal of Physics: Conference Series 2613, № 1 (2023): 012017. http://dx.doi.org/10.1088/1742-6596/2613/1/012017.

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Abstract A novel closed-loop voltage-controlled oscillator (VCO)-based 1-1 sturdy multistage noise-shaping (SMASH) continuous-time ΔΣ ADC is presented in this paper. The proposed architecture uses VCOs as integrators and puts them in a closed loop to suppress the VCO nonlinearity. The multi-bit quantization is employed in the proposed architecture so that the requirement of a high over-sampling ratio (OSR) is relaxed while maintaining a high resolution. The architecture has been verified in MATLAB Simulink.

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Kim, Yeonggwang, Hyeongjun Yoo, Je-Ho Ryu, Seungjoo Lee, Jong Hun Lee, and Jinsul Kim. "TransSMPL: Efficient Human Pose Estimation with Pruned and Quantized Transformer Networks." Electronics 13, no. 24 (2024): 4980. https://doi.org/10.3390/electronics13244980.

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Existing Transformers for 3D human pose and shape estimation models often struggle with computational complexity, particularly when handling high-resolution feature maps. These challenges limit their ability to efficiently utilize fine-grained features, leading to suboptimal performance in accurate body reconstruction. In this work, we propose TransSMPL, a novel Transformer framework built upon the SMPL model, specifically designed to address the challenges of computational complexity and inefficient utilization of high-resolution feature maps in 3D human pose and shape estimation. By replacin

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Zhao, Xue Jun, and Yuan Fei Jing. "The Application of Vector Quantization Algorithm in Hyperspectral Image Compression." Advanced Materials Research 756-759 (September 2013): 1479–83. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1479.

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With the development of Aerospace remote sensing technology, the hyperspectral remote sensing technology is widely applied in earth resources detection, environment investigation and military reconnaissance, etc. It is different from multispectral image, hyperspectral image spectrum period is as many as dozens to hundreds of band, with high resolution, large amount of data, corresponding to the data transmission problem, so the hyperspectral image compression is become necessary. In this paper the vector quantization algorithm is applied for hyperspectral image compression, first convert the t

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47

Ahmed, Ahmed Mohammed, Wurod Qasim Mohamed, and Israa Hazem Ali. "Wireless transceiver bit error rate and capacity improvement using advanced decoding techniques." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1633–41. http://dx.doi.org/10.11591/eei.v11i3.3381.

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This paper considers advanced techniques for multiple-input multiple-output (MIMO) detection and decoding techniques to improve bit error rate (BER) and channel capacity. These are requirements for sixth generation (6G) (the next generation) access networks. A parallel decoding and detection scheme and a soft bit decoding scheme are implemented meregely to boost the overall performance of MIMO communication systems. The proposed new system is called the advanced system which comprises the two mentioned advanced techniques of decoding. For simplicity, these advanced techniques are employed and

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48

Ahmed, Mohammed Ahmed, Qasim Mohamed Wurod, and Hazem Ali Israa. "Wireless transceiver bit error rate and capacity improvement using advanced decoding techniques." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1633~1641. https://doi.org/10.11591/eei.v11i3.3381.

Full text

Abstract:

This paper considers advanced techniques for multiple-input multiple-output (MIMO) detection and decoding techniques to improve bit error rate (BER) and channel capacity. These are requirements for sixth generation (6G) (the next generation) access networks. A parallel decoding and detection scheme and a soft bit decoding scheme are implemented meregely to boost the overall performance of MIMO communication systems. The proposed new system is called the advanced system which comprises the two mentioned advanced techniques of decoding. For simplicity, these advanced techniques are employed and

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49

Li, Rui, Jianchao Yang, Zheng Dai, Xingyu Lu, Ke Tan, and Weimin Su. "High-Resolution and Robust One-Bit Direct-of-Arrival Estimation via Reweighted Atomic Norm Estimation." Sensors 24, no. 18 (2024): 5936. http://dx.doi.org/10.3390/s24185936.

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In recent years, one-bit quantization has attracted widespread attention in the field of direction-of-arrival (DOA) estimation as a low-cost and low-power solution. Many researchers have proposed various estimation algorithms for one-bit DOA estimation, among which atomic norm minimization algorithms exhibit particularly attractive performance as gridless estimation algorithms. However, current one-bit DOA algorithms with atomic norm minimization typically rely on approximating the trace function, which is not the optimal approximation and introduces errors, along with resolution limitations.

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Cheng, Ji-Xin, Xiao-Gang Wang, Hai Lin, and Qing-Shi Zhu. "The high resolution spectrum of AsH3 (400) local mode state: symmetry reduction and rotational re-quantization." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 54, no. 12 (1998): 1947–60. http://dx.doi.org/10.1016/s1386-1425(98)00157-7.

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