Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, howe...

Determination of mobile localization with time of arrival (TOA) signal is a requirement in cellular mobile communication. In some of the previous methods, localization with non-line-of-sight (NLOS) paths can lead to large position error. Also for simplicity, in most simulations suppose non stationary actual environments as stationary. This paper proposes (residual test + recursive least square)...

We study the homogenization of stationary compressible Navier–Stokes–Fourier system in a bounded three dimensional domain perforated with large number very tiny holes. Under suitable assumptions imposed on smallness and distribution holes, we show that homogenized limit remains same without

Stationarity of a data set guarantees spatially invariant statistical properties, such as mean, variance, dip or spectrum. Many image processing schemes assume stationary data and consequently do not apply to nonstationary data. However, these processes can be generalized to apply to local-stationary data sets, a type of nonstationary data. We split the local-stationary data into its stationary...

A new approach to Fourier analysis within the context of circuit simulation is presented that is considerably more accurate and flexible than the traditional SPICE approach. It is based on the direct computation of the Fourier integral rather than on the discrete Fourier transform and so it is not subject to aliasing. It can be used to accurately compute a small number of Fourier coefficients f...

We demonstrate the usefulness of some signalprocessing tools for the EISCAT data analysis. These tools are somewhat less classical than the familiar periodogram, squared modulus of the Fourier transform, and therefore not as commonly used in our community. The first is a stationary analysis, ‘‘Thomson’s estimate’’ of the power spectrum. The other two belong to time-frequency analysis: the short...

Electroencephalographic (EEG) signals are generally non-stationary, however, nearly stationary brain responses, such as steady-state visually evoked potentials (SSVEP), can be recorded in response to repetitive stimuli. Although Fourier transform has precise resolution with long time windows (5 or 10 s for instance) to extract SSVEP response (1-100 Hz ranges), its resolution with shorter window...

S-transform is a new time-frequency analysis method, which is deduced from short-time Fourier transform and continue Wavelet transform. It has much better performance than traditional time-frequency method. Therefore, in this paper, the basic principle of is briefly introduced and the relationships between is analyzed by theoretical derivation. According to the simulation experiments, the time-...

Degraded signal has an adverse effect on the performance of the system and therefore it must be removed before further processing of signals. Spectral analysis through the Fourier transform is the simplest way to remove the noise, but it is limited to only stationary signals. Non stationary signals require continuous analysis of the signal in time and frequency domain. Wavelets provide better t...