Surface electromyograms (EMGs) are valuable in the pathophysiological study and clinical treatment for dystonia. These recordings are critically often contaminated by cardiac artefact. Our objective of this study was to evaluate the performance of an adaptive noise cancellation filter in removing electrocardiogram (ECG) interference from surface EMGs recorded from the trapezius muscles of patie...

We consider parameter estimation in linear models when some of the parameters are known to be integers. Such problems arise, for example, in positioning using phase measurements in the global positioning system (GPS.) Given a linear model, we address two problems: 1. The problem of estimating the parameters. 2. The problem of verifying the parameter estimates. Under Gaussian measurement noise: ...

Constrained optimization techniques are studied in this paper for direct design of linear multichannel equalizers. Novel blind algorithms are derived by minimizing the equalizer’s output variance subject to appropriate constraints. The constraints are chosen to guarantee no desired signal cancellation, and their parameters are jointly optimized to maximize the signal component at the output. Th...

Adaptive nonlinear filtering plays an important role in audio signal processing and echo control. In this contribution a nonlinear system identification method is proposed. The setup is built using adaptive Volterra filters of second and third order with the same memory length. The adaptation is achieved using a Normalized Least Mean Square algorithm with a proper selected stepsize parameter fo...

The aim of the given paper is a development of the direct approach used for the estimation of parameters of a closed-loop discrete-time dynamic system in the case of additive noise with outliers contaminated uniformly in it (Fig. 1). To calculate M -estimates of unknown parameters of such a system by means of processing input and noisy output observations (Fig. 2), the recursive robust H-techni...