This paper proposes a distributed alternating mixed discrete-continuous (DAMDC) algorithm to approach the oracle algorithm based on the diffusion strategy for parameter and spectrum estimation over sensor networks. A least mean squares (LMS) type algorithm that obtains the oracle matrix adaptively is developed and compared with the existing sparsity-aware and conventional algorithms. The propos...

We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. B...

Analysis of the leaky least mean square (LMS) adaptive algorithm has justified the use of a leakage factor in many applications. In this work, a similar leakage factor is introduced in the two-channel LMS and the extended LMS (XLMS) algorithms for use in stereophonic acoustic echo cancellation. This is compared with the alternative of adding random white noise to the input stereo signals. Simul...

In this article we use Monte Carlo analysis to assess the small sample behaviour of the OLS, the weighted least squares (WLS) and the mixed effects metaestimators under several types of effect size heterogeneity, using the bias, the mean squared error and the size and power of the statistical tests as performance indicators. Specifically, we analyse the consequences of heterogeneity in effect s...

It is well known that for continuous time models with a linear drift standard estimation methods yield biased estimators for the mean reversion parameter both in finite discrete samples and in large in-fill samples. In this paper, we obtain two expressions to approximate the bias of the least squares/maximum likelihood estimator of the mean reversion parameter in the Ornstein–Uhlenbeck process ...

Shooter localization in a wireless network of geographically distributed microphones is studied. The arrival time of both the acoustic muzzle blast (MB) from the gunfire and the ballistic shock wave (SW) from the bullet can be registered by the microphone nodes and considered as measurements. To relax the requirements on accurate node clocks, the approach to base the localization on the time di...

We describe a family of object detectors that provides state-of-the-art error rates on several important datasets including INRIA people and PASCAL VOC’06 and VOC’07. The method builds on a number of recent advances. It uses the Latent SVM learning framework and a rich visual feature set that incorporates Histogram of Oriented Gradient, Local Binary Pattern and Local Ternary Pattern descriptors...

The stability of the signed regressor variant of least mean square (LMS) adaptation is found to be heavily dependent on the characteristics of the input sequence. Averaging theory is used to derive a persistence of excitation condition which guarantees exponential stability of the signed regressor algorithm. Failure to meet this condition (which is not equivalent to persistent excitation for LM...

This paper deals with the analysis of adaptive Volterra filters, driven by the LMS algorithm, in the finite-alphabet inputs case. A tailored approach for the input context is presented and used to analyze the behavior of this nonlinear adaptive filter. Complete and rigorous mean square analysis is provided without any constraining independence assumption. Exact transient and steadystate perform...

As an important biological signal, electrocardiogram (ECG) signals provide a valuable basis for the clinical diagnosis and treatment of several diseases. However, its reference significance is based on the effective acquisition and correct recognition of ECG signals. In fact, this mV-level weak signal can be easily affected by various interferences caused by the power of magnetic field, patient...