The newly proposed l1 norm constraint zero-point attraction Least Mean Square algorithm (ZA-LMS) demonstrates excellent performance on exact sparse system identification. However, ZA-LMS has less advantage against standard LMS when the system is near sparse. Thus, in this paper, firstly the near sparse system modeling by Generalized Gaussian Distribution is recommended, where the sparsity is de...

This paper presents a new method for variable step size for LMS algorithm. The proposed algorithm is based on an absolute mean of estimation current and prior error vector. It is called New Varying Step Size LMS Algorithm (NVSSLMS). The main goal of this algorithm is performance enhancement of adaptive echo cancellation system. The proposed time varying step size method begins the learning proc...

To enhance instruction in higher education, many universities in the Middle East have chosen to introduce learning management systems (LMS) to their institutions. However, this new educational technology is not being used at its full potential and faces resistance from faculty members. To investigate this phenomenon, we conducted an empirical research study to uncover factors influencing facult...

Gynaecological leiomyosarcoma (gLMS) represent a heterogeneous group of soft tissue sarcoma, characterized by rare incidence, high aggressiveness and propensity to infiltrate secondary organs, poor prognosis and lethality, because of the lack of biological mechanisms that underlying their progression and effective pharmaceutical treatments. This study was focused on some of the aspects of progr...

We consider a time varying wireless fading channel, equalized by an LMS Decision Feedback equalizer (DFE). We study how well this equalizer tracks the optimal MMSEDFE (Wiener) equalizer. We model the channel by an Autoregressive (AR) process. Then the LMS equalizer and the AR process are jointly approximated by the solution of a system of ODEs (ordinary differential equations). Using these ODEs...

Two halide sensitive acridinium ̄uorophores have been synthesised and immobilised in a hydrophilic copolymer. Thin ®lms of the copolymers swell in aqueous media allowing dye ̄uorescence to be dynamically quenched by the di€usion of halide ions. The new sensor ®lms have been characterised in terms of their sensitivity and selectivity towards halide and are compared to ®lms containing both bound ...

Although the real reproducing kernels are used in an increasing number of machine learning problems, complex kernels have not, yet, been used, in spite of their potential interest in applications such as communications. In this work, we focus our attention on the complex gaussian kernel and its possible application in the complex Kernel LMS algorithm. In order to derive the gradients needed to ...

Lateral medullary syndrome (LMS) is an ischemic disease of the medulla oblongata, which involves the territory of the posterior inferior cerebellar artery. Lateral medullary syndrome is often missed as the cause of autonomic dysregulation in patients with recent brain stem stroke. Due to the location of the baroreceptor regulatory center in the lateral medulla oblongata, patients with LMS occas...

IT-Unterstützung im Lernprozess ist ein Schlüsselfaktor für den Erfolg innovativer Lehr-/Lernszenarien. Notwendige Voraussetzung hierfür ist die sinngetreue Nutzung von Learning Management Systemen (LMS) durch den Lernenden, um den Lernerfolg in innovativen Lehr-/Lernszenarien sicherzustellen. Dennoch gibt es bislang kaum Erkenntnisse, was die sinngetreue Nutzung von LMS beeinflusst. Im ersten ...

The least-mean-square (LMS) estimator is a nonlinear estimator with information dependencies spanning the entire set of data fed into it. The traditional analysis techniques which are used to model this estimator obscure this, restricting the estimator to the finite set of data sufficient to span the length of its filter. The finite Wiener filter is thus often considered a bound on the performa...