Now showing items 1-6 of 6
Framework for online superimposed event detection by sequential Monte Carlo methods
In this paper, we consider online seperation and detection of superimposed events by applying particle filtering. We concentrate on a model where a background process, represented by a 1D-signal, is superimposed by an ...
An empirical eigenvalue-threshold test for sparsity level estimation from compressed measurements
Compressed sensing allows for a significant reduction of the number of measurements when the signal of interest is of a sparse nature. Most computationally efficient algorithms for signal recovery rely on some knowledge ...
A wavelet based recursive reconstruction algorithm for linear measurements
A recursive algorithm is proposed to obtain an efficient regularized least squares solution to large linear system of equations which arises in many physical measurement models. The algorithm recursively updates the solution ...
Markov modulated periodic arrival process offered to an ATM multiplexer
When a superposition of on/off sources is offered to a deterministic server, a particular queueing system arises whose analysis has a significant role in ATM based networks. Periodic cell generation during active times is ...
Adaptive filtering approaches for non-Gaussian stable processes
A large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this paper, α-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian ...
Superimposed event detection by sequential Monte Carlo methods
In this paper, we consider the detection of rare events by applying particle filtering. We model the rare event as an AR signal superposed on a background signal. The activation and deactivation times of the AR-signal are ...