In this correspondence, we analyze the effects of noisy links on steady-state performance diffusion least-mean-square (LMS) adaptive networks. Using established weighted spatial-temporal energy conservation argument, derive a variance relation which contains moments that represent links. We evaluate these and closed-form expressions for mean-square deviation (MSD), excess error (EMSE) (MSE) to explain at each individual node. The derived expressions, supported by simulations, reveal unlike...

This paper presents a game-theoretic decentralized electric vehicle charging schedule for minimizing the customers' payments, maximizing grid efficiency, and providing maximum potential capacity ancillary services. Most of available methods assume that customers are rational, there is low-latency perfect two-way communication infrastructure without communication/computation limitation between distribution company all customers, they have knowledge about system parameters. To avoid these...

In this paper, we consider the demand response problem in smart grid consisting of a retailer and multiple residential consumers, where determines consumers' payments based on their power consumption profile. Our aim is to propose fully distributed algorithm that able optimize aggregate cost, utility, retailer's profit simultaneously. To end, first formulate consumer-side trend as constrained convex optimization adaptive diffusion solve it. addition, design one-leader N-follower Stackelberg...

In this study, an improved artificial intelligence algorithms augmented Internet of Things (IoT)-based maximum power point tracking (MPPT) for photovoltaic (PV) system has been proposed. This will facilitate preventive maintenance, fault detection, and historical analysis the plant in addition to real-time monitoring. Further, simulation results validate performance suggested method. To demonstrate superiority proposed MPPT algorithm over current methods, such as cuckoo search incremental...

Recently proposed adaptive networks assume perfect communication among the nodes. In this correspondence, we extend existing analysis to study performance of incremental least mean square (LMS) in a more realistic case which links between nodes are considered noisy. More precisely, using weighted spatial-temporal energy conservation relation, arrive variance relation contains moments that represent effects noisy links. We evaluate these and derive closed-form expressions for mean-square...

In this study, the authors propose a robust adaptive algorithm for frequency estimation in three‐phase power systems when voltage readings are corrupted by random noise sources. The proposed employs Clarke's transformed (a complex signal) and augmented statistics to deal with both of balanced unbalanced system conditions. To derive algorithm, widely linear predictive model is assumed signal where related parameters model. estimate noisy reading, they utilise notions maximum correntropy...

Many problems in multiagent networks can be solved through distributed learning (state estimation) of linear dynamical systems. In this paper, we develop a partial-diffusion Kalman filtering (PDKF) algorithm, as fully solution for state estimation the with limited communication resources. PDKF every agent (node) is allowed to share only subset its intermediate estimate vectors neighbors at each iteration, reducing amount internode communications. We analyze stability algorithm and show that...

A novel pricing and scheduling mechanism is proposed here for Plug-in electric vehicles (PEVs) charging/discharging to track synchronize with a renewable power generation pattern.Moreover, the can be used in demand-side management ancillary service applications, respectively peak shaving frequency regulation responding.We design fully distributed stochastic optimization using Bayesian pure strategic repeated game by which PEVs optimally schedule their demands.We also use mixed...

Joint energy consumption and trading management is still a major challenge in smart (micro) grids. The main goal of solving such problems to flatten the aggregate power consumption-generation curve increase local direct among participants as much possible. Here, an inclusive formulation for micro/nano-grid (M/NG) proposed this article. Subsequently, holistic solution jointly optimizing internal external grid including several M/NGs provided. As problem computationally intractable, approach...

SUMMARY In this paper, we study the effect of noisy channels on transient performance diffusion adaptive network with least‐mean squares (LMS) learning rule. We first drive update equation LMS which incorporates effects channels. Then, using framework fundamental weighted energy conservation relation, derive closed‐form expressions for curves in terms mean‐square deviation and excess error. also find mean stability bounds step‐size show that although affect network, are same form as ideal...

In this paper the authors propose an adaptive estimation algorithm for in-network processing of complex signals over distributed networks. proposed algorithm, as incremental augmented least mean square (IAC-LMS) nodes network are allowed to collaborate via cooperation mode exploit spatial dimension; while at same time equipped with LMS learning rules endow adaptation. The have extracted closed-form expressions that show how IAC-LMS performs in steady-state. further derived required...

Recently proposed distributed adaptive estimation algorithms for wireless sensor networks (WSNs) do not consider errors due to noisy links, which occur during the transmission of local estimates between sensors. In this paper, we study effect links on performance incremental least-mean-square (DILMS) algorithm case Gaussian regressors. More specifically, derive theoretical relations explain how steady-state DILMS (in terms mean-square deviation (MSD), excess error (EMSE), and (MSE)) is...

In extracellular neural recording experiments, detecting spikes is an important step for reliable information decoding. A successful implementation in integrated circuits can achieve substantial data volume reduction, potentially enabling a wireless operation and closed-loop system. this paper, we report 16-channel spike detection chip based on customized method named as exponential component-polynomial component (EC-PC) algorithm. This algorithm features prediction of by applying...

Partial diffusion-based recursive least squares (PDRLS) is an effective way of lowering computational load and power consumption in adaptive network implementation. In this method, every single node distributes a fraction its intermediate vector estimate with immediate neighbours at each iteration. study, the authors examine steady-state performance PDRLS algorithm presence noisy links by means energy conservation argument. They consider mean-square-deviation (MSD) as metric derive...

The article studies the steady-state performance of a diffusion least-mean squares (LMS) adaptive network with imperfect communications where topology is random (links may fail at times) and communication in channels corrupted by additive noise. Using established weighted spatial–temporal energy conservation argument, authors derive variance relation which contains moments that represent effects noisy links topology. evaluate these closed-form expressions for mean-square deviation, excess...

Demand side energy consumption scheduling is a well-known issue in the smart grid research area. However, there lack of comprehensive method to manage demand and consumer behavior order obtain an optimum solution. The needs address several aspects, including scale-free requirement distributed nature problem, consideration renewable resources, allowing consumers sell electricity back main grid, adaptivity local change solution point. In addition, model should allow compensation ensurance...

Demand-side management (DSM) involves a group of programs, initiatives, and technologies designed to encourage consumers modify their level pattern electricity usage. This is performed following the methods such as financial incentives behavioral change through education. While objective DSM achieve balance between energy production demand, effective efficient implementation program rests within use emerging Internet-of-Things (IoT) concept for online interactions. Here, novel framework...

Naturally complex-valued information or those presented in complex domain are effectively processed by an augmented least-mean-square (ACLMS) algorithm. In some applications, the ACLMS algorithm may be too computationally- and memory-intensive to implement. this paper, a new algorithm, termed partial-update (PU-ACLMS) is proposed, where only fraction of coefficient set selected update at each iteration. Doing so, two types schemes referred as sequential stochastic partial-updates, reduce...

Purpose This paper aims to propose a new approach for determining decoupling point in leagile chain, based on Lean and agile criteria regarding market customer demands internal capabilities of the chain with ultimate goal fulfilling needs increasing profit. Design/methodology/approach In approach, have been defined assessing effectiveness efficiency supply chain. The ratios calculated processes using input- output-oriented Banker, Charnes Cooper (BCC) methods, respectively. Based results,...

We study the effect of fading in communication channels between sensor nodes on performance incremental least mean square (ILMS) algorithm, and derive steady state metrics, including mean-square deviation (MSD), excess error (EMSE) (MSE). obtain conditions for convergence ILMS algorithm show that presence channels, is asymptotically biased. Furthermore, dynamic range stability depends only channel gain, under simplifying technical assumptions, we MSD, EMSE, MSE are non-decreasing functions...

The performance of a partial diffusion Kalman filtering (PDKF) algorithm for the networks with noisy links is studied here. A closed-form expression steady-state mean square deviation then derived and theoretically shown that when are noisy, communication-performance tradeoff, reported PDKF algorithm, does not hold. Additionally, optimal selection combination weights investigated, rule along an adaptive implementation motivated. results confirm theoretical outcome.