PROCEDURE FOR INCREASING SPECTRUM ACCURACY

• US 20090192742A1
• Filed: 01/30/2008
• Published: 07/30/2009
• Est. Priority Date: 01/30/2008
• Status: Abandoned Application

• Current Assignee: Mensur Omerbashich
• Original Assignee: Mensur Omerbashich
• Inventors: Omerbashich, Mensur
• Application Number:
  US12/022,409
• Publication Number:
  US 20090192742A1
• Time in Patent Office: Days
• US Class Current: 702/76
• CPC Class Codes: G01V 7/00 Measuring gravitational fields or waves; Gravimetric prospecting or detecting
• CPC Class Codes: G06F 17/141 Discrete Fourier transforms

Abstract

The method patented enables increase in reliability of periodicity estimates, and consequently of the natural band (of an object; of a body; of a system; etc.) definition too. The patented method is based on the least squares spectral analysis (LSSA) method. The LSSA has been proven over the past thirty years to be fully able of replacing the Fourier and Fourier-based spectral analysis methods (as the most used methods of spectral analysis in all sciences). The here patented method then uses this known feature of the LSSA as a reliable periodicity estimator, and expands its application by claiming that periodicity estimates generally (in all sciences and in all situations) could be improved by removing a number of measurements from the original dataset. Thus, by removing the least reliable (where ‘least’ is according to some, e.g., well-known, criteria) measurements from the dataset of interest, one can estimate periodicities in any (complete or not) type of a numerical record to the logically greatest extent possible.

Claims

1. By using the described procedure (i.e., by the removal of up to 50% of the least reliable data values), the spectrum of a input numerical dataset can be made up to 50% more reliable when compared to other procedures, notably those based on and required for the Fourier spectral analysis and its derivatives as the currently most used of all spectral analysis methods in all sciences.

2. The patented data processing approach (to preparing data for feeding data into the spectral analysis algorithm) represents the simplest approach of all for achieving the most reliable results achievable using any spectral analysis method or derivative.

3. The spectrum obtained in the here described manner, in both its periodicity-estimates as well as spectral-magnitudes advantages (over the Fourier method and its derivatives), when applied onto problems faced with in physical sciences, enable most rigorous spectral analyses.