Zero Crossing Digital Phase Locked Loop with Arc Sine block (AS-ZCDPLL) is used to linearize the phase difference detection, and enhance the loop performance. The loop has faster acquisition, less steady state phase error, and wider locking range compared to the conventional ZCDPLL. This work presents a Zero Crossing Digital Phase Locked Loop with Arc Sine block (ZCDPLL-AS). The performance of ...

The blind equalizer relies on the knowledge of signal’s constellation and its statistics to perform equalization. The major drawback is that the blind equalizer will typically take a longer time to converge as compared to a trained equalizer. Variable Step-Size LMS (VSLMS) algorithms have been introduced to optimize the speed and steady-state error. The relationships between the a priori and a ...

This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) an...

In this paper, we consider the steady state mean square error (MSE) analysis for 2-D LMS adaptive filtering algorithm in which the filter’s weights are updated along both vertical and horizontal directions as a doubly-indexed dynamical system. The MSE analysis is conducted using the well-known independence assumption. First we show that computation of the weight-error covariance matrix for doub...

This paper develops a framework for the mean-square analysis of adaptive lters with general data and error nonlinearities. The approach relies on energy conservation arguments and is carried out without restrictions on the probability distribution of the input sequence. In particular, for adaptive lters with diagonal matrix nonlinearities, we provide closed form expressions for the steady-state...

In this paper, a Proportional-Derivative and Integral (PD-I) type Fuzzy-Neural Network Controller (FNNC) based on Sugeno fuzzy model is proposed for brushless DC drives to achieve satisfied performance under steady state and transient conditions. The proposed FNNC uses the speed error, change of error and the error integral as inputs. While the PD-FNNC is activated in transient states, the PI-F...

This paper develops a result on the design of robust steady-state estimator for a class of uncertain discrete-time systems with Markovian jump parameters. This result extends the steady-state Kalman filter to the case of norm-bounded time-varying uncertainties in the state and measurement equations as well as jumping parameters. We derive a linear state estimator such that the estimation-error ...

A group of mobile robots can localize cooperatively, using relative position and absolute orientation measurements, fused through an extended Kalman filter (ekf). The topology of the graph of relative measurements is known to affect the steady state value of the position error covariance matrix. Classes of sensor graphs are identified, for which tight bounds for the trace of the covariance matr...

In this paper, a new method based on genetic-fuzzy algorithm for multi-objective optimization is proposed. This method is successfully applied to several multi-objective optimization problems. Two examples are presented: the first example is the optimization of two nonlinear mathematical functions and the second one is the design of PI controller for control of an induction motor drive supplie...