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The generative priors of pre-trained latent diffusion models (DMs) have demonstrated great potential to enhance the visual quality of image super-resolution (SR) results. However, the noise sampling process in DMs introduces randomness in…

Image and Video Processing · Electrical Eng. & Systems 2024-09-26 Lingchen Sun , Rongyuan Wu , Jie Liang , Zhengqiang Zhang , Hongwei Yong , Lei Zhang

The paper studies the problem of filtering a discrete-time linear system observed by a network of sensors. The sensors share a common communication medium to the estimator and transmission is bit and power budgeted. Under the assumption of…

Information Theory · Computer Science 2009-10-07 S. Kar , B. Sinopoli , J. M. F. Moura

The relation between rate distortion function (RDF) and Bayesian filtering theory is discussed. The relation is established by imposing a causal or realizability constraint on the reconstruction conditional distribution of the RDF, leading…

Information Theory · Computer Science 2012-04-16 Photios A. Stavrou , Charalambos D. Charalambous , Christos K. Kourtellaris

Time series forecasting (TSF) is critical across domains such as finance, meteorology, and energy. While extending the lookback window theoretically provides richer historical context, in practice, it often introduces irrelevant noise and…

Machine Learning · Computer Science 2026-04-03 Xiang Ao , Yinyu Tan , Mengru Chen

Time is at a premium for recurrent network dynamics, and particularly so when they are stochastic and correlated: the quality of inference from such dynamics fundamentally depends on how fast the neural circuit generates new samples from…

Neurons and Cognition · Quantitative Biology 2014-04-24 Guillaume Hennequin , Laurence Aitchison , Máté Lengyel

Representing a continuous-time signal by a set of samples is a classical problem in signal processing. We study this problem under the additional constraint that the samples are quantized or compressed in a lossy manner under a limited…

Information Theory · Computer Science 2018-04-12 Alon Kipnis , Yonina C. Eldar , Andrea J. Goldsmith

Current-steering (CS) digital-to-analog converters (DACs) generate analog signals by combining weighted current sources. Ideally, the current sources are combined at each switching instant simultaneously. However, this is not true in…

Signal Processing · Electrical Eng. & Systems 2022-03-18 Daniel Beauchamp , Keith M. Chugg

Transient signals are often composed of a series of modes that have multivalued time-dependent instantaneous frequency (IF), which brings challenges to the development of signal processing technology. Fortunately, the group delay (GD) of…

Signal Processing · Electrical Eng. & Systems 2022-02-23 Haoran Dong , Gang Yu

We consider the problem of joint source-channel coding for semantic communication from a rateless perspective, the purpose of which is to settle the balance between reliability (distortion/perception) and effectiveness (rate) of…

Information Retrieval · Computer Science 2025-01-23 Cheng Peng , Rulong Wang , Yong Xiao

In this paper we invoke a nonanticipative information Rate Distortion Function (RDF) for sources with memory, and we analyze its importance in probabilistic matching of the source to the channel so that transmission of a symbol-by-symbol…

Information Theory · Computer Science 2013-04-26 Christos Kourtellaris , Charalambos D. Charalambous , Photios A. Stavrou

In this paper, we consider the mismatched rate-distortion problem, in which the encoding is done using a codebook, and the encoder chooses the minimum-distortion codeword according to a mismatched distortion function that differs from the…

Information Theory · Computer Science 2022-12-20 Millen Kanabar , Jonathan Scarlett

This paper derives novel results on the characterization of the the causal information rate-distortion function (IRDF) $R_{c}^{it}(D)$ for arbitrarily-distributed one-sided stationary $\kappa$-th order Markov source x(1),x(2),.... It is…

Information Theory · Computer Science 2018-04-12 Milan S. Derpich , Marco A. Guerrero , Jan Østergaard

In some practical learning tasks, such as traffic video analysis, the number of available training samples is restricted by different factors, such as limited communication bandwidth and computation power. Determinantal Point Process (DPP)…

Machine Learning · Computer Science 2023-08-17 Xiwen Chen , Huayu Li , Rahul Amin , Abolfazl Razi

A time series consists of a series of values or events obtained over repeated measurements in time. Analysis of time series represents and important tool in many application areas, such as stock market analysis, process and quality control,…

Artificial Intelligence · Computer Science 2013-12-30 Vladimir Kurbalija , Miloš Radovanović , Zoltan Geler , Mirjana Ivanović

Too high sampling rate is the bottleneck to wideband spectrum sensing for cognitive radio in mobile communication. Compressed sensing (CS) is introduced to transfer the sampling burden. The standard sparse signal recovery of CS does not…

Information Theory · Computer Science 2011-06-21 Yipeng Liu , Qun Wan

We consider the recovery of a continuous-time Wiener process from a quantized or lossy compressed version of its uniform samples under limited bitrate and sampling rate. We derive a closed form expression for the optimal tradeoff among…

Information Theory · Computer Science 2018-07-27 Alon Kipnis , Andrea J. Goldsmith , Yonina C. Eldar

Randomly evolving systems composed by elements which interact among each other have always been of great interest in several scientific fields. This work deals with the synchronization phenomenon, that could be roughly defined as the…

Probability · Mathematics 2017-12-18 Giacomo Aletti , Irene Crimaldi , Andrea Ghiglietti

Accurate modelling of redshift-space distortions (RSD) is challenging in the non-linear regime for two-point statistics e.g. the two-point correlation function (2PCF). We take a different perspective to split the galaxy density field…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-14 Enrique Paillas , Yan-Chuan Cai , Nelson Padilla , Ariel Sánchez

Random sampling is a technique for signal acquisition which is gaining popularity in practical signal processing systems. Nowadays, event-driven analog-to-digital converters make random sampling feasible in practical applications. A process…

Data Structures and Algorithms · Computer Science 2015-10-08 Jacek Pierzchlewski , Thomas Arildsen

The rate-distortion saddle-point problem considered by Lapidoth (1997) consists in finding the minimum rate to compress an arbitrary ergodic source when one is constrained to use a random Gaussian codebook and minimum (Euclidean) distance…

Information Theory · Computer Science 2018-09-03 Lin Zhou , Vincent Y. F. Tan , Mehul Motani