Bioclimatic conditions of the Lower Silesia region (South-West Poland) from 1966 to 2017
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This report describes additional experiments with LP-TRAPs -- speech features derived from autoregressive model applied to approximate temporal evolution of speech spectra in critical band-sized frequency sub-bands. The importance of free parameters, such ...
Frequency Domain Linear Prediction (FDLP) represents the technique for approximating temporal envelopes of a signal using autoregressive models. In this paper, we propose a wide-band audio coding system exploiting FDLP. Specifically, FDLP is applied on cri ...
The problem of estimating and predicting Origin-Destination (OD) tables is known to be important and difficult. In the specific context of Intelligent Transportation Systems (ITS), the dynamic nature of the problem and the real-time requirements make it ev ...
Frequency Domain Linear Prediction (FDLP) represents the technique for approximating temporal envelopes of a signal using autoregressive models. In this paper, we propose a wide-band audio coding system exploiting FDLP. Specifically, FDLP is applied on cri ...
The development of a hydrological forecasting model is conditioned by the available data collected in the entire hydrological catchment for which discharge has to be predicted. The forecast quality not only depends on the available historical data but also ...
Based on almost seven years of continuous measurements, we have analysed in detail the influence of occupancy patterns, indoor temperature and outdoor climate parameters (temperature, wind speed and direction, relative humidity and rainfall) on window open ...
An approach to analysis of time series of edge localized modes (ELMs) is proposed. It is based on the use of the autoregressive moving average model, which decomposes time series into deterministic and noise components. Despite the inclusion of nonlinearit ...
Models dealing directly with the raw acoustic speech signal are an alternative to conventional feature-based HMMs. A popular way to model the raw speech signal is by means of an autoregressive (AR) process. Being too simple to cope with the nonlinearity of ...
Autoregressive modeling is applied for approximating the temporal evolution of spectral density in critical-band-sized sub-bands of a segment of speech signal. The generalized autocorrelation linear predictive technique allows for a compromise between fitt ...
Autoregressive modeling is applied for approximating the temporal evolution of spectral density in critical-band-sized sub-bands of a segment of speech signal. The generalized autocorrelation linear predictive technique allows for a compromise between fitt ...