Flux-barrier permanent magnet Vernier motors are among the latest magnetic motors developed and optimized in the industry. In these motors, the arrangement of magnets plays a critical role and significantly impacts on...
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This article formulates interactive adversarial differential graphical games for synchronization control of multiagent systems(MASs) subject to adversarial inputs interacting with the systems through topology communic...
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This article formulates interactive adversarial differential graphical games for synchronization control of multiagent systems(MASs) subject to adversarial inputs interacting with the systems through topology communications. Local control and interactive adversarial inputs affect each agent's local synchronization error via local networks. The distributed global Nash equilibrium(NE) solutions are guaranteed in the games by solving the optimal control input of each agent and the worst-case adversarial input based solely on local states and communications. The asymptotic stability of the local synchronization error dynamics and the NE are guaranteed. Furthermore, the authors devise a data-driven online reinforcement learning(RL) algorithm that only computes the distributed Nash control online using system trajectory data, eliminating the need for explicit system dynamics. A simulation-based example validates the game and algorithm.
The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text ***,BERT’s ...
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The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text ***,BERT’s size and computational demands limit its practicality,especially in resource-constrained *** research compresses the BERT base model for Bengali emotion classification through knowledge distillation(KD),pruning,and quantization *** Bengali being the sixth most spoken language globally,NLP research in this area is *** approach addresses this gap by creating an efficient BERT-based model for Bengali *** have explored 20 combinations for KD,quantization,and pruning,resulting in improved speedup,fewer parameters,and reduced memory *** best results demonstrate significant improvements in both speed and *** instance,in the case of mBERT,we achieved a 3.87×speedup and 4×compression ratio with a combination of Distil+Prune+Quant that reduced parameters from 178 to 46 M,while the memory size decreased from 711 to 178 *** results offer scalable solutions for NLP tasks in various languages and advance the field of model compression,making these models suitable for real-world applications in resource-limited environments.
The variability of the output power of distributed renewable energy sources(DRESs)that originate from the fastchanging climatic conditions can negatively affect the grid ***,grid operators have incorporated ramp-rate ...
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The variability of the output power of distributed renewable energy sources(DRESs)that originate from the fastchanging climatic conditions can negatively affect the grid ***,grid operators have incorporated ramp-rate limitations(RRLs)for the injected DRES power in the grid *** the DRES penetration levels increase,the mitigation of high-power ramps is no longer considered as a system support function but rather an ancillary service(AS).Energy storage systems(ESSs)coordinated by RR control algorithms are often applied to mitigate these power ***,no unified definition of active power ramps,which is essential to treat the RRL as AS,currently *** paper assesses the various definitions for ramp-rate RR and proposes RRL method control for a central battery ESS(BESS)in distribution systems(DSs).The ultimate objective is to restrain high-power ramps at the distribution transformer level so that RRL can be traded as AS to the upstream transmission system(TS).The proposed control is based on the direct control of theΔP/Δt,which means that the control parameters are directly correlated with the RR requirements included in the grid *** addition,a novel method for restoring the state of charge(So C)within a specific range following a high ramp-up/down event is ***,a parametric method for estimating the sizing of central BESSs(BESS sizing for short)is *** BESS sizing is determined by considering the RR requirements,the DRES units,and the load mix of the examined *** BESS sizing is directly related to the constant RR achieved using the proposed ***,the proposed methodologies are validated through simulations in MATLAB/Simulink and laboratory tests in a commercially available BESS.
The vast deployment of UAVs as base stations in 5 G and beyond, provides a facile accessibility to the users as an advantage and the flight constraints as deficiencies. In this work, we study a multi-tier cellula...
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Direct training of Spiking Neural Networks (SNNs) is a challenging task because of their inherent temporality. Added to it, the vanilla Back-propagation based methods are not applicable either, due to the non-differen...
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Direct training of Spiking Neural Networks (SNNs) is a challenging task because of their inherent temporality. Added to it, the vanilla Back-propagation based methods are not applicable either, due to the non-differentiability of the spikes in SNNs. Surrogate-Derivative based methods with Backpropagation Through Time (BPTT) address these direct training challenges quite well;however, such methods are not neuromorphic-hardware friendly for the On-chip training of SNNs. Recently formalized Three-Factor based Rules (TFR) for direct local-training of SNNs are neuromorphic-hardware friendly;however, they do not effectively leverage the depth of the SNN architectures (we show it empirically here), thus, are limited. In this work, we present an improved version of a conventional three-factor rule, for local learning in SNNs which effectively leverages depth - in the context of learning features hierarchically. Taking inspiration from the Back-propagation algorithm, we theoretically derive our improved, local, three-factor based learning method, named DALTON (Deep LocAl Learning via local WeighTs and SurrOgate-Derivative TraNsfer), which employs weights and surrogate-derivative transfer from the local layers. Along the lines of TFR, our proposed method DALTON is also amenable to the neuromorphic-hardware implementation. Through extensive experiments on static (MNIST, FMNIST, & CIFAR10) and event-based (N-MNIST, DVS128-Gesture, & DVSCIFAR10) datasets, we show that our proposed local-learning method DALTON makes effective use of the depth in Convolutional SNNs, compared to the vanilla TFR implementation. IEEE
The printed circuit boards (PCBs) should be inspected during the manufacturing process to minimize defects such as printing errors, incorrect component selections, and incorrect soldering. Convolutional neural network...
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The security of digital images transmitted via the Internet or other public media is of the utmost *** encryption is a method of keeping an image secure while it travels across a non-secure communication medium where ...
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The security of digital images transmitted via the Internet or other public media is of the utmost *** encryption is a method of keeping an image secure while it travels across a non-secure communication medium where it could be intercepted by unauthorized *** study provides an approach to color image encryption that could find practical use in various *** proposed method,which combines four chaotic systems,employs singular value decomposition and a chaotic sequence,making it both secure and *** unified average change intensity,the number of pixels’change rate,information entropy analysis,correlation coefficient analysis,compression friendliness,and security against brute force,statistical analysis and differential attacks are all used to evaluate the algorithm’s *** a thorough investigation of the experimental data,it is concluded that the proposed image encryption approach is secure against a wide range of attacks and provides superior compression friendliness when compared to chaos-based alternatives.
In this paper we show a polar coding scheme for the deletion channel with a probability of error that decays roughly like 2-√Λ, where Λ is the length of the codeword. That is, the same decay rate as that of seminal...
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Video captioning is the process of automatically generating natural language descriptions of video content. Historically, most video captioning methods have relied on extending Sequence-to-Sequence (Seq2Seq) models. H...
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