We propose a joint filtering and factorization algorithm to recover latent structure from noisy speech. We incorporate the minimum variance distortionless response (MVDR) formulation within the non-negative matrix factorization (NMF) framework to derive a single, unified cost function for both filtering and factorization. Minimizing this cost function jointly optimizes three quantities – a filt...

To overcome the performance degradation in the presence of steering vector mismatches, strict restrictions on the number of available snapshots, and numerous interferences, a novel beamforming approach based on nonlinear least-square support vector regression machine (LS-SVR) is derived in this paper. In this approach, the conventional linearly constrained minimum variance cost function used by...

ABSTRACT This paper present on simple method for multiplier-free finite impulse response (FIR) filter design based on the cascade of comb and linearly tapered comb filters. The stopband frequency determines the length of the comb filter. The method is used for narrowband filters where the passband frequency is not more than 0.1 of the stopband frequency. The sharpening technique is used to sati...

State estimation is a fundamental task in plethora of applications. Two important classes linear minimum mean square error (MMSE) estimators are Wiener filters (WFs) and Kalman (KFs), the latter being recursive form former for discrete state-space (LDSS) dynamic models. The set uncorrelation conditions regarding states measurements which allows to formulate general KF has been recently introduc...

Abstract This paper is concerned with the linear unbiased minimum variance estimation problem for discrete-time stochastic linear control systems with one-step random delay and inconsecutive packet dropout. A new model is developed to describe the phenomena of the one-step delay and inconsecutive packet dropout by employing a Bernoulli distributed stochastic variable. Based on the model, a recu...

In this paper, the amplitude and variance-constrained LQG control is considered for a plant given by discretetime ARMAX model. The minimization of constrained quadratic cost is approached by Kalman filter, approximation of the probability density function (pdf) of the state by the Gaussian one and by by tuning of the Lagrange multiplier. The obtained optimization algorithm is simulated for seco...

Mean–variance portfolio optimization problems often involve separable nonconvex terms, including penalties on capital gains, integer share constraints, and minimum nonzero position trade sizes. We propose a heuristic algorithm for such based the alternating direction method of multipliers (ADMM). This allows solve times in tens to hundreds milliseconds with around 1000 securities 100 risk facto...