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This paper presents a study of the transient performance of the speed and position sensorless control of an interior permanent magnet synchronous motor (IPMSM) based on back-electromotive force (back-EMF) estimation method in the rotor reference frame. The fundamental characteristics of the estimated back-EMF, position and speed components using mathematical models of the IPMSM are analyzed. The analyzed...
Currently the number of applications where the data generation function is not known has been growing, making necessary the use of non-parametric estimation techniques to describe such model. Therefore, relevant questions emerge regarding the quality of the model that represents some dataset and how to quantify this quality. This article aims to evaluate some of the measurements presented in the literature...
When local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/tracking purposes. Failure to make...
In this paper, qualification of the p-cascade tuned filter capacity estimation is presented for radio communication systems using multiposition phase-shift keyed signals with n-discrete states. It is shown that the capacity will be limited to the resolution time of linear systems that are present in the RCS linear radio-frequency section and that are an integral part of channel. The method of estimating...
Big data analytics (BDA) applications are software applications that process huge amounts of data using large-scale parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open source BDA processing framework, which implements the MapReduce programming paradigm. In many cases, BDA jobs are continuous and not mutually separated. Existing work on processing jobs in sequence...
Estimation of the channel distortion characteristics is of crucial importance for realizing a reliable communication. In order to estimate the channel, a received signal is sampled at some rate. The Nyquist rate is widely used notion to determine the sampling rate of the received signal. On the other hand, Vetterli introduced the concept of rate of innovation that is the degree of freedom of the signal...
The paper addresses the problem of available bandwidth measurement in IP networks, with special attention to situations where the available bandwidth undergoes quick variations and needs be accurately tracked. The proposed solution is based on a Kalman filtering of the interarrival times of probing packet pairs, according to a Probe Gap Model and is therefore less invasive than alternative solutions...
Host virtualization allows data centers to live migrate an entire Virtual Machine (VM) to support data center maintenance and workload balancing. Live VM Migration can consume nearly the entire bandwidth which impacts the performance of competing flows in the network. Knowing the cost of VM Migration propels data center admins to intelligently reserve minimum bandwidth required to ensure a network-aware...
We consider the effective bandwidth (EB) estimation in the networks with the regenerative input. Based on the Lindley's-type recursion for the workload process in discrete and continuous time, we apply a large deviation approach to construct a regenerative estimate of the required EB in the nodes of tandem queuing networks. Simulation shows that the regenerative estimator overestimates the EB, while...
Due to the various navigation signals and wide processing bandwidth, high resolution is required for the narrow band interference estimation in multi-system navigation receiver. The parametric spectral estimator especially the autoregressive (AR) model estimator is used to make high resolution compared to the conventional non-parametric spectral estimator. The properties of both methods are discussed...
We propose a broadcast method for Delay Tolerant Networks (DTNs) to achieve small latency for message diffusion in a congested situation. In the existing DTN broadcast methods, nodes tend to transfer a limited variant of messages to the contacted nodes, and thus cause an inefficient bandwidth use. That leads to a large latency of message diffusion. This paper proposes a new transfer message selection...
Linear prediction methods, based on a Hankel data matrix, suffer from subspace leakage and degraded resolution when applied to data models that do not result in a mode matrix with Vandermonde structure, such as the constant-Q model. In the absence of noise, the Vandermonde structure ensures the equivalence between the number of backscattered signals and the rank of the data matrix. This paper first...
In this paper, we analyze the performance of time delay estimation with regards to different pulse shape in UWB indoor navigation. For the performance of time delay estimation, the Cramer-Rao Lower Bound (CRLB) criterion is used and the performance is analyzed under various criteria of pulse shape, such as pulse period, order of differentiation, and the effective pulse width. Moreover, the reasonability...
This work investigates three major phenomena of range estimation performance for a passive RFID system that transmits power-optimized waveforms (POWs). The shape of the POW, nonlinear charge pump reflections, and frequency-flat multipath environments are investigated. A maximum-likelihood (ML) range estimator analyzes the backscattered signal from a passive RFID tag that includes the POW as a carrier...
To estimate the density f of a conditional expectation μ(Z) = E[X|Z], Steckley and Henderson (2003) sample independent copies Z1,…,Zm; then, conditional on Zi, they sample n independent samples of X, and their sample mean ̄Xi is an approximate sample of μ(Zi). For a kernel density estimate ̂f of f based on such samples and a bandwidth (smoothing parameter) h, they consider the mean integrated squared...
In the paper the variable bandwidth M-estimators of the partial linear models are discussed. The variable bandwidth M-estimation of the unknown function and local variable bandwidth M-estimators of the unknown parameter is proposed by local linear method. Under the assumptions, the consistence and the asymptotic normality of the estimators of the unknown function and the unknown parameter are proofed...
Improving on recent work on joint source-filter analysis of speech waveforms, we explore improvements to an autoregressive model with exogenous inputs represented by flexible basis functions. Following a brief review of the maximum likelihood estimators of the model parameters, the Cramér-Rao bounds are derived to provide evidence for the challenging nature of estimating source and filter characteristics...
In peer-to-peer video-on-demand (P2P VoD) streaming services, a video server load is reduced by peers who cache data of the viewed videos and send these data to other peers instead of the video server. Although FIFO is typically used as the caching algorithm, it is not efficient for using upload bandwidth of the peers because the peers can cache the data of unpopular videos and cannot be requested...
This work proposes a novel priority based resource management framework for multimedia applications in distributed collaborative environment. Due to the dynamic nature of the collaborative environment, sometimes the network could be lightly loaded and sometimes highly congested. Moreover, application priority might be changed by the user dynamically. In this dynamic environment, Quality of Experience...
We present a probabilistic localization and orientation estimation method for mobile agents equipped with omnidirectional vision. In our appearance-based framework, a scene is learned in an offline step by modeling the variation of the image energy in the frequency domain via Gaussian process regression. The metric localization of novel views is then solved by maximizing the joint predictive probability...
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