Grouped sparsity algorithm for multichannel intracardiac ECG synchronization

In this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a three-stage algorithm. We first compute a robust estimate of the derivative of the data to remove low-frequency perturbations. Then we provide a grouped-sparse representation of the data, by means of the Group LASSO, to ensure that all the electrical spikes are simultaneously detected. Finally, a post-processing step, based on a variance analysis, is performed to discard false alarms. Preliminary results on real data for sinus rhythm and atrial fibrillation show the potential of this approach.

Low-complexity timing synchronization scheme for MB-OFDM UWB receiver based on sign-bit

A unified low complexity sign-bit correlation based symbol timing synchronization scheme for Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) Ultra Wideband (UWB) receiver system is proposed. By using the time domain sequence of the packet/frame synchronization preamble, the proposed scheme is in charge of detecting the upcoming MB-OFDM symbol and it estimates the exact boundary of the start of Fast Fourier Transform (FFT) window. The proposed algorithm is implemented by using an efficient Hardware-Software co-simulation methodology. The effectiveness of the proposed synchronization scheme and the optimization criteria is confirmed by hardware implementation results.

Temporal task allocation in periodic environments. An approach based on synchronization

In this paper, we study a robot swarm that has to perform task allocation in an environment that features periodic properties. In this environment, tasks appear in different areas following periodic temporal patterns. The swarm has to reallocate its workforce periodically, performing a temporal task allocation that must be synchronized with the environment to be effective. We tackle temporal task allocation using methods and concepts that we borrow from the signal processing literature. In particular, we propose a distributed temporal task allocation algorithm that synchronizes robots of the swarm with the environment and with each other. In this algorithm, robots use only local information and a simple visual communication protocol based on light blinking. Our results show that a robot swarm that uses the proposed temporal task allocation algorithm performs considerably more tasks than a swarm that uses a greedy algorithm.