A reduced complexity realisation for the normalised constant modulus algorithm (NCMA) and its soft criterion satisfaction (SCS) version is proposed based on selective partial updating. The computational complexity of NCMA and SCS is reduced by updating a block of equaliser parameters at every iteration rather than the entire equaliser. This results in a smaller number of multiplications for upd...

It is well known that a linear operator equation of the first kind, with an operator having nonclosed range, is ill-posed, that is, the solution depends discontinuously on the data. Tikhonov's method for approximating the solution depends on the choice of a positive parameter which effects a trade-off between fidelity and regularity in the approximate solution. If the parameter is chosen accord...

The t-value of a (t,m, s)-net is an important criterion of point sets for quasiMonte Carlo integration, and many point sets are constructed in terms of tvalues, as this leads to small integration error bounds. Recently, Matsumoto, Saito, and Matoba proposed the Walsh figure of merit (WAFOM) as a quickly computable criterion of point sets that ensure higher order convergence for function classes...

By coupling the wavelet transform with a particular nonlinear shrinking function, the Red-telescopic optimal wavelet estimation of the risk (TOWER) method is introduced for removing noise from signals. It is shown that the method yields convergence of the 2 risk to the actual solution with optimal rate. Moreover, the method is proved to be asymptotically efficient when the regularization parame...

An improved genetic algorithm is proposed to solve optimal problems, which is based on fixed point algorithms of continuous self-mapping in Euclidean space. The algorithm operates on a simplicial subdivision of searching space and generates the integer labels at the vertices, then, applied crossover operators and increasing dimension operators according to these labels. In this case, it is used...

The EM algorithm is the standard tool for maximum likelihood estimation in )nite mixture models. The main drawbacks of the EM algorithm are its slow convergence and the dependence of the solution on both the stopping criterion and the initial values used. The problems referring to slow convergence and the choice of a stopping criterion have been dealt with in literature and the present paper de...

We consider orthonormal expansions where the basis functions are governed by some free parameters. If the basis functions adhere to a certain differential or difference equation, then an expression can be given for a specific enforced convergence rate criterion as well as an upper bound for the quadratic truncation error. This expression is a function of the free parameters and some simple sign...

Although there are many versions of evolutionary algorithms that are tailored to multi–criteria optimization, theoretical results are apparently not yet available. Here, it is shown that results known from the theory of evolutionary algorithms in case of single criterion optimization do not carry over to the multi–criterion case. At first, three different step size rules are investigated numeri...

Mean squared error (MSE) has been the most widely used tool to solve the linear filter estimation or system identification problem. However, MSE gives biased results when the input signals are noisy. This paper presents a novel stochastic gradient algorithm based on the recently proposed error whitening criterion (EWC) to tackle the problem of linear filter estimation in the presence of additiv...

We derive a new criterion for a real-valued function u to be in the Sobolev space W 1,2(Rn). This criterion consists of comparing the value of a functional ∫ f (u) with the values of the same functional applied to convolutions of u with a Dirac sequence. The difference of these values converges to zero as the convolutions approach u, and we prove that the rate of convergence to zero is connecte...