A computationally efficient DAB bit-stream processor

This paper describes an MPEG (moving pictures expert group) audio layer II - LFE (lower frequency extension) bit-stream processor targeting DAB (digital audio broadcasting) receivers that will handle the decoding of the frames in a computationally efficient manner to provide a synthesis sub-band filter with the reconstructed sub-band samples. Focus is given to the frequency sample reconstruction part, which handles the re-quantization and re-scaling of the samples once the necessary information is extracted from the frame. The comparison to a direct implementation of the frequency sample reconstruction block is carried out to prove increased computational efficiency.

Forecasting overseas visitors into the United Kingdom using continuous time and autoregressive fractional integrated moving average models with discrete data

This paper applies Gaussian estimation methods to continuous time models for modelling overseas visitors into the UK. The use of continuous time modelling is widely used in economics and finance but not in tourism forecasting. Using monthly data for 1986–2010, various continuous time models are estimated and compared to autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models. Dynamic forecasts are obtained over different periods. The empirical results show that the ARIMA model performs very well, but that the constant elasticity of variance (CEV) continuous time model has the lowest root mean squared error (RMSE) over a short period.