This paper studies the problem of designing robust H∞ filters for linear uncertain systems. The uncertainty parameters are assumed to be time-varying, unknown, but bounded, which appear affinely in the matrices of system models. An adaptive mechanism is introduced to construct novel filters with variable gains, which can reduce the conservativeness of traditional robust H∞ filters. The proposed...

This paper explores the use of imprecise computing to develop digital filters with adaptive length in order to meet real-time constraints. A large-order filter typically provides better filtering but takes longer to compute than a low order filter. An adaptive length filter can provide a resource manager with alternatives that can be used if resources become scarce. This paper discusses the use...

One of the main objectives within the adaptive signal processing is the noise suppression, i.e. the detection of information bearing signal in noise. Adaptive filter application ANC (Adaptive Noise Cancellation) using adaptive Filter algorithm is an important basis for signal processing. The device automatically filters out the components of the signal which are not related to the orignal signa...

An adaptive noise cancellation scheme for speech processing is described, in which adaptive filters operate in frequency–limited sub–bands. Previously the filters had been distributed in a linear fashion in the frequency domain. This work investigates the effects of spacing the filters more in sympathy with the signal power and spectral characteristics. It is found that improvements in signal–t...

An adaptive noise cancellation scheme for speech processing is proposed. In this, the adaptive filters are implemented in frequency–limited sub–bands. In previous work, the filters had been distributed in a linear fashion in the frequency domain. This work investigates the effects of spacing the filters more in sympathy with the signal power and spectral characteristics. It emerges that improve...

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 application of multidimensional adaptive non-linear filters for interpolation of interlaced imagery is investigated. Moreover, a new scheme for combination of several data estimates by weighting based on one-sample correlation is proposed. This technique achieves superior performance when combining vertical and temporal signals at a moderate complexity increase. In the spatial domain, one-d...

One of the main problem in biomedical data processing like electrocardiography is the separation of the wanted signal from noises caused by power line interference, external electromagnetic fields and random body movements and respiration. Different types of digital filters are used to remove signal components from unwanted frequency ranges. It is difficult to apply filters with fixed coefficie...

Weighted Median (WM) filters have attracted a growing number of interest in the past few years. They inherent the robustness and edge preserving capability of the classical median filter and resemble linear FIR filters in certain properties. Furthermore, WM filters belong to the broad class of nonlinear filters called stack filters. This enables the use of the tools developed for the latter cla...

A comparison of signal-to-noise ratios and rise times was performed on several myoelectric filters used for muscle-force estimation and prosthesis control. Linear, averaging, and adaptive filters were compared using single as well as multiple electrode pairs (spatial filtering). The filters were matched for having the same rise time (0-95%) and the signal-to-noise ratios were measured off-line ...