Up-sampling Factor Research Articles

Enhancement in screening throughput and density of combinatorial libraries using wavelet analysis

We report an approach to increase the measurement rate in the real-time monitoring of parallel combinatorial reactions with a single scanning device. The wavelet transform is applied to collected data to reduce the integration time needed to achieve a predetermined signal-to-noise. As an example, we analyzed Raman spectra of diphenyl carbonate, one of the starting components in a melt-polymerization reaction of polycarbonate performed on combinatorial (150 μL volume) scale. The time reduction after the wavelet analysis of each measured spectrum permitted sampling of full spectra from each combinatorial reaction with an up-sampling factor N=20–90. Such up-sampling capability is critical for increasing the density of combinatorial libraries during their dynamic analysis where each library element is measured multiple times during combinatorial reactions.

Design of cosine-modulated filterbanks for partial spectrum reconstruction

In this paper, we present a new technique to design filterbanks that allows the partial reconstruction of the spectrum of a signal. In several applications, there is the need of either decreasing the sampling rate of a signal preserving part of its spectrum or increasing the sampling rate with minimum spectrum degradation. In this paper, we will develop a method based on cosine-modulated filterbanks to accomplish this task. An analysis filterbank is used to divide the spectrum into subbands. Another filterbank, with a different number of channels, is used to reconstruct the spectrum contained in part of (or all) the subbands. The ratio between the input and output sampling rates is equal to the ratio between the analysis downsampling and synthesis upsampling factors. The problem becomes that of designing the prototypes of the analysis and synthesis filterbanks. Several numerical examples of filterbanks design are presented.

Model-based filter banks and corresponding subband coding systems: Multirate state-space approach

A new model-based filter bank configuration is proposed in this work and its corresponding subband coding schemes are also discussed. The proposed filter bank system is developed specifically for the autoregressive input signals with a consideration of subband noises. First, the analysis filters are designed on the basis of the conventional frequency splitting algorithms. Next, the synthesis filter is derived according to the composite effects of the AR input signal, the allpass analysis filters, and the white subband noises. State-space framework is used to describe the analysis section. Hence, a new multirate Kalman synthesis filter is derived to achieve optimal signal reconstruction. Computer simulations reveal that perfect reconstruction is achieved for the clean subband case and optimal reconstruction is obtained when the corrupting noises exist in the subband paths. In addition, the subband coding systems pertaining to the proposed model-based filter bank configuration have the advantage of better reconstructed speech quality and possess a flexible subband number and down-/up-sampling factor.

Optimal FIR pre- and postfilters for decimation and interpolation of random signals

A technique for the design of finite-impulse-response (FIR) filters for decimation and interpolation in multirate systems is introduced. FIR prefilters and postfilters that jointly minimize a frequency-weighted mean-square error between the original and reconstructed signals can be designed. There is no need for ideal filter prototypes: the optimal pre-postfilter pair is determined from the signal and noise spectra and the up-sampling and down-sampling factors. Some examples of image and speech processing show that the mean square optimal filter pair leads to typical SNR improvements of 2-6 dB, in comparison to other commonly used filters.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>