this paper presents a comparative analysis between two current control strategies, constant source power and generalized fryze current, used in active power filter (apf) applications having three different modulation methods. the hysteresis band (hb) and first-order delta-sigma modulation (dsm) as well as the second-order dsm is applied. the power section of the active power filter is viewed as...

This article adresses parameter estimation with moment-based stochastic filters that only heed the first two moments of the state densities. This approximation provides good results in numerous cases. However, due to missing linear correlation between diffusion parameters and expected states, Bayesian estimation of diffusion parameters such as volatility is not possible. While other filters ove...

A new filtering algorithm, adaptive square root cubature Kalman filter-Kalman filter (SRCKF-KF) is proposed to reduce the problems of amount of calculation, complex formula-transform, low accuracy, poor convergence or even divergence. The method uses cubature Kalman filter (CKF) to estimate the nonlinear states of model while its linear states are estimated by the Kalman filter (KF). The simula...

Terrestrial LiDAR provides many disciplines with an effective and efficient means of producing realistic three-dimensional models of real world objects. With the advent of mobile terrestrial LiDAR, this ability has been expanded to include the rapid collection of three-dimensional models of large urban scenes. For all its usefulness, it does have drawbacks. One of the major problems faced by th...

Compared to normal learning algorithms, for example backpropagation, Kalman filter-based algorithm has some better properties, such as faster convergence, although this algorithm is more complex and sensitive to the nature of noises. In this paper, extended Kalman filter is applied to train state-space recurrent neural networks for nonlinear system identification. In order to improve robustness...

In this paper, an improved Precise Point Positioning GPS/MEMS-based integrated system is introduced for precise positioning applications. Un-differenced ionosphere-free linear combinations of carrier phase and code measurements are processed. Tropospheric delay, satellite clock, ocean loading, Earth tide, carrier-phase windup, relativity, and satellite and receiver antenna phase-center variatio...

Abstract: Incremental Net Pro (IncNet Pro) with local learning feature and statistically controlled growing and pruning of the network is introduced. The architecture of the net is based on RBF networks. Extended Kalman Filter algorithm and its new fast version is proposed and used as learning algorithm. IncNet Pro is similar to the Resource Allocation Network described by Platt in the main ide...

This paper describes a Kalman filter for the real-time estimation of a rigid body orientation from measurements of acceleration, angular velocity and magnetic field strength. A quaternion representation of the orientation is computationally effective and avoids problems with singularities. The nonlinear relationship between estimated orientation and expected measurement prevent the usage of a c...

Kalman filter based training algorithms for recurrent neural networks provide a clever alternative to the standard backpropagation in time. However, these algorithms do not take into account the optimization of the hidden state variables of the recurrent network. In addition, their formulation requires Jacobian evaluations over the entire network, adding to their computational complexity. In th...