N dimensional non-linear, static, adaptive digital filter design using d scale non-uniform sampling

Abstract

The present invention is a filter design that extracts information from a signal by employing D scale nonuniform sampling. In one embodiment a D scale multiresolution sampler, filter bank router, filter bank sampler controller, phase shifter, and consolidator constitute a maximal arrangement for a D scale FIR / IIR filter design.

Description

[0001]This application is a Continuation of U.S. patent application Ser. No. 10 / 250,830, filed on Jan. 30, 2004, which is now U.S. Pat. No. ______ issued on ______, which is the National Phase of International Application No. PCT / US02 / 00940 filed Jan. 4, 2002, which is based on Application Ser. No. 60 / 259,961, filed Jan. 5, 2001.FIELD OF THE INVENTION[0002]This invention concerns N dimensional digital filter design in its broadest sense. Filters are used to restrict or sculpt 1D signals, 2D / 3D images or more abstract N dimensional objects that traverse communications channels. They are also used for data smoothing and prediction, signal detection and noise reduction applications.[0003]Typically, digital filters rely on the Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) linear mathematical models. Data inputs to these models are almost always assumed to be uniformly spaced sample points. Various filter architectures use these underlying models to accommodate divers...

AI Technical Summary

Benefits of technology

[0032]This filter design invention, named the D digital filter, extracts that additional information from the non-uniform sampling of signal volatility to improve the effectiveness and performance of the filter's intended application. The performance measure or metric used depends on the application. For example, for standard noise filtering and signal smoothing applications, the D filter is designed to sharpen spectrum cutoff and to minimize ripples in the frequency spectrum, while preserving phase. Or, for adaptive applications, the D filter is designed to accurately or closely track changes from a reference condition, with fast response time. FIG. 5 illustrates the information flow through a filter with sampling incorporated.

[0056]1. Enhanced IIR digital filtering by increasing its stability while minimizing the number of tap weights. Stability is the main constraint to wider applications of current state-of-the-art IIR filters.

[0057]2. Sharper or finer “sculpting” of a channel's bandwidth to achieve the same filtering effect as the usual designs, but with reduced number of tap weights. Alternately, the same number of taps as in a standard filter yields heightened filtering impact.

[0059]4. Evolutionary design is built on the existing framework of current digital filters. This reduces implementation risk as well as to preserve the investment in the installed base.

Problems solved by technology

a. Linear systems models.

b. Approximation of the Fourier Transform via the Discrete Fourier Transform (DFT). This is a fair approximation under best signal condition, and potentially considerably worse for transient and non-stationary signals.

c. Generally periodic, stationary signals.

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