This paper focuses on analysing multiple time series relationships such as correlations between them. We develop a solution for the Connectiomics contest dataset of fluorescence imaging of neural activity recordings – the aim is reconstruction of the wiring between brain neurons. The model is implemented to achieve high evaluation score. Our model took the fourth place in this contest. The perf...

We describe a method for prediction of genes that encode the RNA component of the signal recognition particle (SRP). A heuristic search for the strongly conserved helix 8 motif of SRP RNA is combined with covariance models that are based on previously known SRP RNA sequences. By screening available genomic sequences we have identified a large number of novel SRP RNA genes and we can account for...

Attenuating random noise with a prediction lter in the time-space domain generally produces results similar to those of predictions done in the frequency-space domain. However, in the presence of moderate-to high-amplitude noise, time-space, or t-x prediction passes less random noise than does frequency-space, or f-x prediction. The f-x prediction may also produce false events in the presence o...

A joint analysis-synthesis framework is developed for the compressive sensing (CS) recovery of speech signals. The signal is assumed to be sparse in the residual domain with the linear prediction filter used as the sparse transformation. Importantly this transform is not known apriori, since estimating the predictor filter requires the knowledge of the signal. Two prediction filters, one comb f...

Past, Prediction Error, Prediction with Finite Past, Solution of the Normal Equation, The Triplet a,c,k, Lattice Filters for Prediction, Positivity and Stability, S-Step Prediction, The Maximum Entropy Method, Wold Decomposition and Related Problems, Appendix on Stability, Problem. It deals with the prediction theory providing one of the most illuminating applications of the results given in th...

A filter for universal real-time prediction of band-limited signals is presented. The filter consists of multiple time-delayed feedback terms in order to accomplish anticipatory coupling, which again leads to a negative group delay for frequencies in the baseband. The universality of the filter arises from its property that it does not rely on a specific model of the signal. Specifically, as lo...

This paper describes a speech-coding algorithm that we develop recently. We call it M&CELP VOCODER. It is based on the traditional linear prediction vocoder. The excitation is constructed by not usually one of either periodic pulse or white noise, but the mixture of periodic feature-waveform (from predict error) and periodic pulse and white noise passed high pass filter in voiced speech section...