The recent popularity of deep neural networks (DNNs) has generated considerable research interest in performing DNN-related computation efficiently. However, the primary focus is usually very narrow and limited to (i) inference - i.e. how efficiently execute already trained models (ii) image classification as benchmark for evaluation. Our goal this work break myopic view by proposing a new suite DNN training, called TBD <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...

In future cell-free (or cell-less) wireless networks, a large number of devices in geographical area will be served simultaneously non-orthogonal multiple access scenarios by distributed points (APs), which coordinate with centralized processing pool. For such network static predefined beamforming design, we first derive closed-form expression uplink outage probability for user/device. To reduce the complexity joint received signals presence and APs, propose novel dynamic architecture. this...

The large language models GPT-4 Vision and Large Language Assistant are capable of understanding accurately differentiating between benign lesions melanoma, indicating potential incorporation into dermatologic care, medical research, education.

In a cell-free network, large number of mobile devices are served simultaneously by several base stations (BSs)/access points(APs) using the same time/frequency resources. However, this creates high signal processing demands (e.g., for beamforming) at transmitters and receivers. work, we develop centralized distributed deep reinforcement learning (DRL)-based methods to optimize beamforming uplink network. First, propose fully method (i.e., learning) that uses Deep Deterministic Policy...

We present a unified model for connected antenna arrays with large number of tightly integrated (i.e., coupled) antennas in compact space within the context massive multiple-input multiple-output (MIMO) communication. refer to this system as tightly-coupled MIMO. From an information-theoretic perspective, scaling design MIMO systems terms antennas, operational bandwidth, and form factor was not addressed prior art. investigate open research problem using physically consistent modeling...

The recent popularity of deep neural networks (DNNs) has generated a lot research interest in performing DNN-related computation efficiently. However, the primary focus is usually very narrow and limited to (i) inference -- i.e. how efficiently execute already trained models (ii) image classification as benchmark for evaluation. Our goal this work break myopic view by proposing new DNN training, called TBD (TBD short Training Benchmark DNNs), that uses representative set cover wide range...

Current algorithms for deep learning probably cannot run in the brain because they rely on weight transport, where forward-path neurons transmit their synaptic weights to a feedback path, way that is likely impossible biologically. An algorithm called alignment achieves without transport by using random weights, but it performs poorly hard visual-recognition tasks. Here we describe two mechanisms - neural circuit mirror and modification of an proposed Kolen Pollack 1994 both which let path...

Data-driven machine learning (ML) is promoted as one potential technology to be used in next-generation wireless systems. This led a large body of research work that applies ML techniques solve problems different layers the transmission link. However, most these applications rely on supervised which assumes source (training) and target (test) data are independent identically distributed (i.i.d). assumption often violated real world due domain or distribution shifts between data. Thus, it...

We propose a novel antenna clustering-based method for simultaneous wireless information and power transfer (SWIPT) in multiple-input multiple-output (MIMO) full-duplex (FD) system. For point-to-point communication set up, the proposed enables device with multiple antennas to simultaneously transmit harvest energy using same time-frequency resources. And transmitting receives from harvesting (EH) device. This is achieved by clustering into two MIMO subsystems: one transmission (IT) another...

Most research studies on deep learning (DL) applied to the physical layer of wireless communication do not put forward critical role accuracy-generalization trade-off in developing and evaluating practical algorithms. To highlight disadvantage this common practice, we revisit a data decoding example from one first papers introducing DL-based end-to-end systems community promoting use artificial intelligence (AI)/DL for layer. We then two key trade-offs designing DL models communication,...

This paper introduces a novel information-theoretic approach for studying the effects of mutual coupling (MC), between transmit and receive antennas, on overall performance single-input-single-output (SISO) near-field communications (NFC). By incorporating finite antenna size constraint using Chu's theory under assumption canonical-minimum scattering (CMS), we derive MC two radiating volumes fixed sizes. Expressions self impedances are obtained by use reciprocity theorem. Based...

This study has been performed to determine the influence of rotating shift work on physical working capacity Tunisian nurses and design recommendations managers so that they implement effective preventive measures.It is a cross-sectional using standardized questionnaire many tests representative sample 1181 nursing assistants from two university hospital centers school Medicine Monastir located in Sahel. 293 participants have recruited by stratified random sampling according gender...

We present a Reinforcement Learning (RL) methodology to bypass Google reCAPTCHA v3. formulate the problem as grid world where agent learns how move mouse and click on button receive high score. study performance of when we vary cell size show that drops takes big steps toward goal. Finally, used divide conquer strategy defeat system for any resolution. Our proposed method achieves success rate 97.4% 100x100 96.7% 1000x1000 screen

Using ideas from Chu and Bode/Fano theories, we characterize the maximum achievable rate over single-input single-output wireless communication channels under a restriction on antenna size at receiver. By employing circuit-theoretic multiport models for radio systems, derive information-theoretic limits of compact antennas. We first describe an equivalent Chu's circuit physical realizability conditions its reflection coefficient. Such design allows us to subsequently compute given receive...

This paper investigates distributed estimation problems with factorized structures over factor graphs. By building upon the recent progress in approximate message passing (AMP) paradigm, this extends vector AMP (VAMP) algorithm to scenario where multiple agents collaboratively estimate same signal using different measurement channels. We do so by deriving new collaborative linear minimum mean square error (LMMSE) messages within steps through passing. The — coined D-VAMP allows be...