1 Facultatea de Electronică şi Telecomunicaţii, Departamentul Comunicaţii Bd. V. Pârvan Nr. 2, 300223 Timişoara, e-mail: [email protected] 2 e-mail: [email protected] 3 e-mail: [email protected] Abstract – The paper addresses the problem of estimating the parameters of chirp signals embedded in Gaussian noise. We consider an estimation method based on an approximate linear s...

In this paper, we discuss regularisation in online/sequential learning algorithms. In environments where data arrives sequentially, techniques such as cross-validation to achieve regularisation or model selection are not possible. Further, bootstrapping to determine a confidence level is not practical. To surmount these problems, a minimum variance estimation approach that makes use of the exte...

In this work, we propose a distributed adaptive high-gain extended Kalman filtering approach for nonlinear systems. Specifically, we consider a class of nonlinear systems that are composed of several subsystems interacting with each other via their states. In the proposed approach, an adaptive high-gain extended Kalman filter is designed for each subsystem. The distributed Kalman filters commun...

In this paper, the extended Kalman filtering problem is investigated for a class of nonlinear systems with multiple missing measurements over a finite horizon. Both deterministic and stochastic nonlinearities are included in the system model, where the stochastic nonlinearities are described by statistical means that could reflect the multiplicative stochastic disturbances. The phenomenon of me...

This paper elaborates how the time update of the continuous-discrete extended Kalman-Filter (EKF) can be computed in the most efficient way. The specific structure of the EKF-moment differential equations leads to a new Taylor-Heun-approximation of the nonlinear vector field. Furthermore, the order of consistency and stability behavior of the outlined procedure is investigated. The results are ...

Some signals, such as in radar systems, communication systems, and neural systems, are transmitted as periodic pulse trains. If more than one pulse train is transmitted over the same communication channel, a challenge is to separate them for source identification at the receiver. This is known as pulse train deinterleaving and is clearly a fundamental problem in the study of discrete-event syst...

Most neural networks used today rely on rigid, fixed-architecture networks and/or slow, gradient descent-based training algorithms (e. g. backpropagation). In this paper, we propose a new neural network learning architecture to counter these problems. Namely, we combine (1) flexible cascade neural networks, which dynamically adjust the size of the neural network as part of the learning process,...

The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user. In this paper, we study the filter likelihood technique for estimating the parameters of the model error covariance matrix. The approach is based on computing the likeliho...

High Order Quadrature Amplitude Modulation (QAM) is a high-bandwidth-efficient modulation scheme employed in the wireless communications. For this type of modulation, one of the most important problems is carrier recovery to allow a coherent demodulation. To extract correctly the transmitted symbols as the carrier frequency offset between the transmitter and receiver is inevitable, the receiver...

Lithium-ion batteries have become a chosen energy solution for many types of systems including consumer electronics, electric vehicles, and military and aerospace electronics, due to their high energy density, high galvanic potential, lightness of weight and long lifetimes compared to lead-acid, nickel-cadmium, and nickel-metal-hydride cells. As the demand for lithium-ion batteries increases so...