Results 21 to 30 of about 5,685 (163)
Gradient Estimation for Ultra Low Precision POT and Additive POT Quantization
IEEE Access, 2023 Deep learning networks achieve high accuracy for many classification tasks in computer vision and natural language processing. As these models are usually over-parameterized, the computations and memory required are unsuitable for power-constrained ...
Huruy Tesfai +4 more
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One-bit quantization is good for programmable coding metasurfaces
Science China Information Sciences, 2022 The information-carrying programmable metasurfaces has found widespread applications in communication, sensing, and other related areas. However, there is a fundamental but unresolved problem, i.e., the rigorous understanding of the quantization of metasurface coding.
Shuang, Ya +7 more
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One-bit quantizers for fading channels
CoRR, 2011 4 pages. To be presented at the 2012 International Zurich Seminar on Communications (IZS)
Koch, Tobias, Lapidoth, Amos
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ALigN: A Highly Accurate Adaptive Layerwise Log_2_Lead Quantization of Pre-Trained Neural Networks
IEEE Access, 2020 Deep Neural Networks are one of the machine learning techniques which are increasingly used in a variety of applications. However, the significantly high memory and computation demands of deep neural networks often limit their deployment on embedded ...
Siddharth Gupta +4 more
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SANA: Sensitivity-Aware Neural Architecture Adaptation for Uniform Quantization
Applied Sciences, 2023 Uniform quantization is widely taken as an efficient compression method in practical applications. Despite its merit of having a low computational overhead, uniform quantization fails to preserve sensitive components in neural networks when applied with ...
Mingfei Guo, Zhen Dong, Kurt Keutzer
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1-Bit Reconfigurable Beam Steering Planar Array Antenna Based on Reflectarray Feeding
IEEE Access, 2023 In this paper, we present a method for reducing the quantization lobe in a 1-bit beam steering planar array antenna. The method is inspired by reflectarray feeding in such a way that as we move away from the center of the array, the phase becomes more ...
Pooria Kabiri +2 more
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One-bit Multi-modality Jamming Method against SAR
Leida xuebao, 2022 This paper proposes a one-bit multi-modality jamming method against Synthetic Aperture Radar (SAR). After being intercepted by the jammer, the SAR signal is quantized to one-bit sampling data through comparison with the single-frequency threshold ...
Bo ZHAO, Ji CHEN, Lei HUANG
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Approximation of capacity for ISI channels with one-bit output quantization [PDF]
2015 IEEE International Symposium on Information Theory (ISIT), 2015 Motivated by recent high bandwidth communication systems, Inter-Symbol Interference (ISI) channels with 1-bit quantized output are considered under an average-power-constrained continuous input. While the exact capacity is difficult to characterize, an approximation that matches with the exact channel output up to a probability of error is provided ...
Radha Krishna Ganti +2 more
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Limited feedback in multiple-antenna systems with one-bit quantization [PDF]
2015 49th Asilomar Conference on Signals, Systems and Computers, 2015 Communication systems with low-resolution analog-to-digital-converters (ADCs) can exploit channel state information at the transmitter (CSIT) and receiver. This paper presents initial results on codebook design and performance analysis for limited feedback systems with one-bit ADCs.
Jianhua Mo 0001, Robert W. Heath Jr.
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Evaluation of Model Quantization Method on Vitis-AI for Mitigating Adversarial Examples
IEEE Access, 2023 Adversarial examples (AEs) are typical model evasion attacks and security threats in deep neural networks (DNNs). One of the countermeasures is adversarial training (AT), and it trains DNNs by using a training dataset containing AEs to achieve robustness
Yuta Fukuda +2 more
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