The concept of programmable cascaded low-pass filter for stator flux vector synthesis by ideal integration of stator voltages at any frequency was introduced by Bose and Patel. A new form of implementation of this filter is being proposed here that uses a combination of recurrent neural network trained by Kalman filter and a polynomial neural network. The proposed structure is simple, permits f...

In this contribution a new noise reduction scheme for multi-microphone speech enhancement, called Adaptive Post-filter Extension for Superdirective beamformers (APES), will be introduced, The combination of the superdirective beamformer and the adaptive post-filter has a great potential to suppress diffuse noise. It also outperforms all related algorithms in terms of noise reduction, without in...

In this paper, a new two dimensional (2D) adaptive filter structure is developed. It is based on modeling the impulse response of the 2D IIR systems as a finite linear combination of a set of 2D Laguerre orthonormal functions. When long impulse response system is required to identify, computer simulation shows that the 2D Laguerre filter has better performance than the conventional 2D FIR filte...

Using particle filter to figure visual object tracking, a key problem is to choose appropriate image features as the observation model. In this paper, we present a novel particle filter based object tracking framework via the combination of state and observation optimization. We apply the technique to articulated human movement tracking. Result demonstrates the effectiveness of our method in so...

Median filter is well known for removing impulsive noise and preserving edges. Repeatedly filtering of any one-dimensional signal with a median filter will produce a root signal. Any impulses in the input signal will be removed by sufficient number of passes of median filter, where any root like features in the input signal will be preserved. A signal of finite length will be filtered to a root...

The task of determining the distance from one object to another is important tasks solved in robotics systems. Conventional algorithms rely on an iterative process predicting estimates, which results increased computational burden. Algorithms used robotic systems should require minimal time costs, as well be resistant presence noise. To solve these problems, paper proposes algorithm for Kalman ...