In this paper, a new Iaguerre domain adaptive filter algorithm, which will be refered to as the Laguerre domain adaptive filter II (LDAF It) has been proposed. The performance of the adaptive filtering algorithms simulated for acoustic echo cancellation application. The performances of the algorithm are specified using various quantities. All the results of the work, for different performance q...

This work addresses the problem of signal dependent noise removal in images. An adaptive nonlinear filtering approach in the orthogonal transform domain is proposed and analyzed for several typical noise environments in the DCT domain. Being applied locally, i.e., within a window of small support, DCT is expected to approximate the Karhunen-Loeve decorrelating transform, which enables effective...

Some convergence properties of an adaptive filter structure which employs an analysis filter bank and sparse adaptive subfilters are investigated in this paper. By properly choosing the filter bank and the number of adaptive coefficients, such a structure is capable of modeling any linear system with finite impulse response (FIR). Using the analysis results derived in this paper, an optimizatio...

PURPOSE Photon counting spectral breast CT is feasible in part due to using an adaptive filter. An adaptive filter provides flat x-ray intensity profile and constant x-ray energy spectrum across detector surface, decreases required detector count rate, and eliminates beam hardening artifacts. However, the altered x-ray exposure profiles at the breast and detector surface may influence the distr...

This paper presents a scheme for designing a totally decentralized adaptive stabilizers for a class of large-scale systems with subsystems having arbitrary relative degrees. In the control design, both strong static interactions and weak dynamic interactions are considered. It is shown that with the proposed controller global stability of the overall system and perfect regulation can be guarant...

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...

Adaptive estimation of the state-of-charge (SoC) for batteries is increasingly appealing, thanks to its ability to accommodate uncertain or time-varying model parameters. We propose to improve the adaptive SoC estimation using multiple models in this study, developing a unique algorithm called MMAdaSoC. Specifically, two submodels in state-space form are generated from a modified Nernst battery...

This paper presents an integrated method of the adaptive enhancement for an unsupervised global-to-local segmentation of brain tissues in three-dimensional (3-D) MRI (Magnetic Resonance Imaging) images. Three brain tissues are of interest: CSF (CerebroSpinal Fluid), GM (Gray Matter), WM (White Matter). Firstly, we de-noise the images using a newly proposed versatile wavelet-based filter, and se...

In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms...

While adaptive filtering is in principle intended for tracking non-stationary systems, most adaptive filtering algorithms have been designed for converging to a fixed unknown filter. When actually confronted with a non-stationary environment, they possess just one parameter (stepsize, forgetting factor) to adjust their tracking capability. Virtually the only existing optimal approach is the Kal...