Equation (1) is called the measurement equation. It relates the measured observable variables that provide information on αt. We use Zt ∈ M (pt ×m) to denote the matrix of factor loadings. The Ht ∈M (pt × pt) matrix is the variance-covariance matrix of the measurement noise vector, εt. Equation (2) is called the transition equation. We use Gt ∈ M (m×m) to denote the matrix of factor coefficient...

Model-based feature enhancement is an ASR front-end technique to increase the robustness of the recogniser in noisy environments. However, its MMSE-estimates of the clean speech feature vectors are based only on the static components at the current frame. In this paper, we show how the Kalman filter framework can be seen as a natural extension that incorporates both the current and the previous...

An array of nonidentical and locally connected chaotic biological neurons is modelled by a single representative chaotic neuron model based on an extension of the Hindmarsh-Rose neuron. This model is then employed in conjunction with the unscented Kalman filter to study the associated state estimation problem. The archetypal system, which was deliberately chosen to be chaotic, was corrupted wit...

Recurrent neural networks, in contrast to the classical feedforward neural networks, better handle inputs that have spacetime structure, e.g. symbolic time series. Since the classic gradient methods for recurrent neural network training on longer input sequences converge very poorly and slowly, the alternative approaches are needed. We describe the principles of the training method with the Ext...

In the normal operation conditions of a pico satellite, conventional Unscented Kalman Filter (UKF) gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunction in the estimation system, UKF gives inaccurate results and diverges by time. This study, introduces Robust Unscented Kalman Filter (RUKF) algorithms with the filter gain cor...

This paper presents a novel and cost effective method to be used in the optimization of the Gaussian Frequency Shift Keying (GFSK) at the receiver of the Bluetooth communication system. The proposed method enhances the performance of the noncoherent demodulation schemes by improving the Bit Error Rate (BER) and Frame Error Rate (FER) outcomes. Linear, Extended, and Unscented Kalman Filters are ...

Localizing a vehicle consists in estimating its state by merging data from proprioceptive sensors (inertial measurement unit, gyrometer, odometer, etc.) and exteroceptive sensors (GPS sensor). A well known solution in state estimation is provided by the Kalman filter. But, due to the presence of nonlinearities, the Kalman estimator is applicable only through some alternatives among which the Ex...