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Optimal coding over the additive white Gaussian noise channel under the peak energy constraint is studied when there is noisy feedback over an orthogonal additive white Gaussian noise channel. As shown by Pinsker, under the peak energy…

Information Theory · Computer Science 2011-08-19 Yu Xiang , Young-Han Kim

We investigate and compare the fundamental performance of several distributed learning methods that have been proposed recently. We do this in the context of a distributed version of the classical signal-in-Gaussian-white-noise model, which…

Statistics Theory · Mathematics 2017-11-10 Botond Szabo , Harry van Zanten

Mixed linear regression (MLR) model is among the most exemplary statistical tools for modeling non-linear distributions using a mixture of linear models. When the additive noise in MLR model is Gaussian, Expectation-Maximization (EM)…

Machine Learning · Statistics 2021-05-14 Babak Barazandeh , Ali Ghafelebashi , Meisam Razaviyayn , Ram Sriharsha

We study the rate of decay of the probability of error for distinguishing between a sparse signal with noise, modeled as a sparse mixture, from pure noise. This problem has many applications in signal processing, evolutionary biology,…

Information Theory · Computer Science 2016-12-28 Jonathan G. Ligo , George V. Moustakides , Venugopal V. Veeravalli

We present a mathematical model for communication subject to both network interference and noise. We introduce a framework where the interferers are scattered according to a spatial Poisson process, and are operating asynchronously in a…

Information Theory · Computer Science 2016-11-17 Pedro C. Pinto , Moe Z. Win

Recent diffusion models have achieved promising performances in audio-denoising tasks. The unique property of the reverse process could recover clean signals. However, the distribution of real-world noises does not comply with a single…

Sound · Computer Science 2024-06-14 Pu Wang , Junhui Li , Jialu Li , Liangdong Guo , Youshan Zhang

Image compression is a fundamental research field and many well-known compression standards have been developed for many decades. Recently, learned compression methods exhibit a fast development trend with promising results. However, there…

Image and Video Processing · Electrical Eng. & Systems 2020-03-31 Zhengxue Cheng , Heming Sun , Masaru Takeuchi , Jiro Katto

For multichannel speech enhancement, this letter derives a robust maximum likelihood distortionless response beamformer by modeling speech sparse priors with a complex generalized Gaussian distribution, where we refer to as the CGGD-MLDR…

Audio and Speech Processing · Electrical Eng. & Systems 2021-02-22 Weixin Meng , Chengshi Zheng , Xiaodong Li

Chaotic signals offer promising characteristics for wireless communications due to their wideband nature, low cross-correlation, and sensitivity to initial conditions. Although classical chaotic modulation schemes like Chaos Shift Keying…

Signal Processing · Electrical Eng. & Systems 2024-09-11 Marc Martinez-Gost , Ana Pérez-Neira , Miguel Ángel Lagunas

In this paper, we study a remote source coding scenario in which binary phase shift keying (BPSK) modulation sources are corrupted by additive white Gaussian noise (AWGN). An intermediate node, such as a relay, receives these observations…

Information Theory · Computer Science 2024-05-14 Yi Song , Kai Wan , Zhenyu Liao , Giuseppe Caire

Generative diffusion processes are an emerging and effective tool for image and speech generation. In the existing methods, the underline noise distribution of the diffusion process is Gaussian noise. However, fitting distributions with…

Machine Learning · Computer Science 2021-06-17 Eliya Nachmani , Robin San Roman , Lior Wolf

Best relay selection (BRS) is crucial in enhancing the performance of cooperative networks. In contrast to most previous works, where the guidelines for BRS are limited to Gaussian noise, in this article, we propose a novel relay selection…

Signal Processing · Electrical Eng. & Systems 2019-05-30 Md Sahabul Alam , Georges Kaddoum , Basile L. Agba

Channel estimation is a fundamental task in communication systems and is critical for effective demodulation. While most works deal with a simple scenario where the measurements are corrupted by the additive white Gaussian noise (AWGN),…

Signal Processing · Electrical Eng. & Systems 2024-12-10 Yifan Wang , Chengjie Yu , Jiang Zhu , Fangyong Wang , Xingbin Tu , Yan Wei , Fengzhong Qu

Two decoder structures for coded modulation over the Gaussian and flat fading channels are studied: the maximum likelihood symbol-wise decoder, and the (suboptimal) bit-wise decoder based on the bit-interleaved coded modulation paradigm. We…

Information Theory · Computer Science 2014-04-23 Mikhail Ivanov , Alex Alvarado , Fredrik Brannstrom , Erik Agrell

This letter presents a comparison of exact probability density function with the Gaussian noise approximation in optically pre-amplified DPSK receivers with optical Mach-Zehnder interferometer demodulation (MZI) and balanced detection,…

Optics · Physics 2007-05-23 Xiupu Zhang , Zhenqian Qu , Guodong Zhang , Guangxue Yang

We propose a greedy variational method for decomposing a non-negative multivariate signal as a weighted sum of Gaussians, which, borrowing the terminology from statistics, we refer to as a Gaussian mixture model. Notably, our method has the…

Machine Learning · Statistics 2020-05-21 Gustav Zickert , Can Evren Yarman

The signal demixing problem seeks to separate a superposition of multiple signals into its constituent components. This paper studies a two-stage approach that first decompresses and subsequently deconvolves the noisy and undersampled…

Information Retrieval · Computer Science 2022-05-25 Zhenan Fan , Halyun Jeong , Babhru Joshi , Michael P. Friedlander

Speech enhancement is a critical component of many user-oriented audio applications, yet current systems still suffer from distorted and unnatural outputs. While generative models have shown strong potential in speech synthesis, they are…

Audio and Speech Processing · Electrical Eng. & Systems 2022-02-11 Yen-Ju Lu , Zhong-Qiu Wang , Shinji Watanabe , Alexander Richard , Cheng Yu , Yu Tsao

Noise originating from several sources in a RF environment degrades the performance of communication systems. In wideband systems, such as cognitive radios, noise at the receiver can originate from non-linearity present in the RF front end,…

Signal Processing · Electrical Eng. & Systems 2018-01-31 Adnan Quadri , Mohsen Riahi Manesh , Naima Kaabouch

This work analyzes the high-SNR asymptotic error performance of outage-limited communications with fading, where the number of bits that arrive at the transmitter during any time slot is random but the delivery of bits at the receiver must…

Information Theory · Computer Science 2016-11-17 Somsak Kittipiyakul , Petros Elia , Tara Javidi