Electroencephalogram (EEG) remains the most immediate, simple, and rich source of information for understanding phenomena related to brain electrical activities. It is certainly a source of basic and interesting information to be extracted using specific and appropriate techniques. The most important aspect in processing EEG signals is to use less co-lateral assets and instrumentation in order to carried out a possible diagnosis; this is the approach of early diagnosis. Advanced estimate spectral analysis can reveal new information encompassed in EEG signals by means of specific parameters or indices. The research proposes a multidimensional approach with a combined use of decimated signal diagonalization (DSD) as basis from which it is possible to work by finding appropriate signal windows for revealing expected information and overcoming signal processing limitations encountered in quantitative EEG. Important information, about the state of the patient under observation, must be extracted from calculated DSD bispectrum. For this aim, it is useful to define an assessment index about the dynamic process associated with the analyzed signal. This information is measured by means of entropy, since the degree of order/disorder of the recorded EEG signal will be reflected in the obtained DSD bispectrum. The general advantage of multidimensional approach is to reveal eventual stealth frequencies "in space and in time" giving a topological vision to be correlated to physical areas which these frequencies emerge from. Long term and sleeping EEG recorded are analyzed, and the results obtained are of interest for an accurate diagnosis of the patient's clinical condition.

Although today water is becoming more and more precious, its major waste is caused by transportation. The authorities in charge of the management of water pipes indicate double-digit percentage of waste, sometimes it even exceeds 50% the amount of water mostly lost by inefficiency of distribution waterworks. In this study, the authors present an alternative method of spectral analysis, used for detecting leaks in water pipes, with respect to classical spectral methods as direct Fourier transform/fast Fourier transform. They have used decimated Padè approximant (DPA), where the input time signal points or auto-correlation functions are given via measurements or computations, and the task is to reconstruct the unknown components as the harmonic variables in terms of the fundamental complex frequencies and amplitudes. They have also introduced decimated linear predictor technique as direct consequence of the DPA, since they differ only in one step, namely the calculation of the amplitudes.

No abstract