AlgorithmsLeast squares methodConvergenceRecursive filtersPerturbationsUncertaintyKalman filteringStochastic processesReprintsInitial condition robustnessSufficient conditions are given under which the mean-square error of linear least squares (11s) estimates converges to its true steady-state value despite ...
Further least squares design is compared with least P-th Norm design of Finite Impulse Response (FIR) Filters. Normally optimization algorithms iteratively check the new solutions in order to achieve a true optimum solution. Here the digital filter design and analysis shows various parameters ...
However, such estimators are more general than Belavkin-Kalman and classical Kalman filters. Furthermore, we obtain sufficient conditions ensuring physical realizability of such non-commutative least mean squares estimators. Indeed, this paper shows that the physical realizability of such non-commutative...
Di Napoli, Non-Linear Least-Squares Optimization of Rational Filters for the Solution of Interior Eigenvalue Problems, preprint, arXiv:1704.03255, 2017... J Winkelmann,ED Napoli - 《Frontiers in Applied Mathematics & Statistics》 被引量: 4发表: 2017年 Convergence properties of normalized random in...
Adaptive filters are utilized for non-stationary applications. LSE applied to curve fitting Matlab snippet for implementing Least Estimate to fit a curve is given below. x = -5:.1:5; % set of x- values - known explanatory variables
A theory of linear least-mean-squares equalization in digital data communications operating over two coupled linear dispersive channels, with particular application to dually polarized terrestrial radio systems is presented. We jointly optimize transmitter and receiver matrix filters when the inputs are two...
Thus, the FMH filter output is the median of only M values, which are the outputs of M FIR filters applied to the original data. For an FMH filter of length 2I + 1 with three FIR substructures (M = 3), the data are split into three parts on which the FIR filters are applied. ...
have transmitter and receiver filters that result in a delay. This delay must be accounted for to synchronize the system. In this example, the system delay is introduced without transmit and receive filters. Linear equalization, using the least mean squares (LMS) algorithm, recovers QPSK symbols....
IMD products are a major problem in communication systems because their frequencies fall very close to the fundamental signal, and it is not feasible to implement linear filters that are capable to suppress them. It is customary to measure IMD as a dB ratio between the power of one of the ...
www.BDTIC.com/LINEAR ■ Anti-Aliasing Filters For frequencies up to 0.75fCUTOFF, the passband ripple is ■ Smoothing Filters ± 0.15dB. The gain at fCUTOFF is –1dB and the filter’s ■ Audio Signal Processing stopband attenuation is 80dB at 2.3fCUTOFF. Linear phase , LTC and LT are ...