Inter-regional correlation in tree-growth variations in the western United States, 1513-1964, at ENSO, sunspot, and longer frequency bands

Cross-spectral analysis of regional tree-ring data suggests the spatial pattern of correlation between moisture variations in the Sierra Nevada of central California and in other parts of the western United States is frequency dependent. Short wavelengths (2.8 to 10.7 years), perhaps associated with El Niño/Southern Oscillation, are strongly coherent both to the north (Oregon) and to the south (Southern California). Longer wavelengths (45 to 75 years) are strongly coherent only to the north. Frequency bands corresponding to annual sunspot series were associated with relatively weak patterns of spatial correlation.

Length frequency and growth studies on Cynoglossus macrolepidotus (Bleeker) off Bombay coast

Specimens randomly collected from Sassoon Docks, Bombay, India, at monthly intervals during 1979 to 1981 were considered for age/growth studies. Cynoglossus macrolepidotus, the fish, attained a length of 202 mm at 1 year, 250 mm at 1 1/2 year and 272 mm at 21 months respectively; the maximum length of the fish could be 353 mm and the life span could be 7 years. The scale ring studies showed presence of only 0 to 3+ rings. Majority of the fishes were of 1 and 1+ year class.

Time-frequency spectral estimation of speech

In recent years there has been a growing interest amongst the speech research community into the use of spectral estimators which circumvent the traditional quasi-stationary assumption and provide greater time-frequency (t-f) resolution than conventional spectral estimators, such as the short time Fourier power spectrum (STFPS). One distribution in particular, the Wigner distribution (WD), has attracted considerable interest. However, experimental studies have indicated that, despite its improved t-f resolution, employing the WD as the front end of speech recognition system actually reduces recognition performance; only by explicitly re-introducing t-f smoothing into the WD are recognition rates improved. In this paper we provide an explanation for these findings. By treating the spectral estimation problem as one of optimization of a bias variance trade off, we show why additional t-f smoothing improves recognition rates, despite reducing the t-f resolution of the spectral estimator. A practical adaptive smoothing algorithm is presented, whicy attempts to match the degree of smoothing introduced into the WD with the time varying quasi-stationary regions within the speech waveform. The recognition performance of the resulting adaptively smoothed estimator is found to be comparable to that of conventional filterbank estimators, yet the average temporal sampling rate of the resulting spectral vectors is reduced by around a factor of 10. © 1992.

Frequency-based interpolation of sampled signals with applications in audio restoration

A new interpolation technique has been developed for replacing missing samples in a sampled waveform drawn from a stationary stochastic process, given the power spectrum for the process. The method works with a finite block of data and is based on the assumption that components of the block DFT are Gaussian zero-mean independent random variables with variance proportional to the power spectrum at each frequency value. These assumptions make the interpolator particularly suitable for signals with a sharply-defined harmonic structure, such as audio waveforms recorded from music or voiced speech. Some results are presented and comparisons are made with existing techniques.