Norden E Huang

6381559, Apr 30, 2002

Mar 31, 1999

09/282424

Norden E. Huang - Bethesda MD

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

G06F 1500

702194, 702189, 702 19

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMFs, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMFs. Then, these IMFs, based on and derived from the data, can serve as the basis of that expansion.

6631325, Oct 7, 2003

May 21, 1998

09/082523

Norden Eh Huang - Bethesda MD
Zheng Shen - Etobicoke, CA

The United States as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

G06F 1900

702 3, 702 15

A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMFs, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum.

6738734, May 18, 2004

Dec 10, 2001

10/011206

Norden E. Huang - Bethesda MD

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

H04B 1500

702194, 702179, 708300

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMFs, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMFs. Then, these IMFs, based on and derived from the data, can serve as the basis of that expansion.

6862558, Mar 1, 2005

Feb 13, 2002

10/073957

Norden E. Huang - Bethesda MD, US

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

H04B015/00
G06F019/00

702194, 702179, 708300, 704226

The present invention discloses a computer implemented signal analysis method through the Hilbert-Huang Transformation (HHT) for analyzing acoustical signals, which are assumed to be nonlinear and nonstationary. The Empirical Decomposition Method (EMD) and the Hilbert Spectral Analysis (HSA) are used to obtain the HHT. Essentially, the acoustical signal will be decomposed into the Intrinsic Mode Function Components (IMFs). Once the invention decomposes the acoustic signal into its constituting components, all operations such as analyzing, identifying, and removing unwanted signals can be performed on these components. Upon transforming the IMFs into Hilbert spectrum, the acoustical signal may be compared with other acoustical signals.

6901353, May 31, 2005

Jul 8, 2003

10/615365

Norden E. Huang - Bethesda MD, US

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

G06F019/00

702189, 702 67, 702104, 702179

This invention presents Normalized Amplitude Hilbert Transform (NAHT) and Normalized Hilbert Transform(NHT), both of which are new methods for computing Instantaneous Frequency. This method is designed specifically to circumvent the limitation set by the Bedorsian and Nuttal Theorems, and to provide a sharp local measure of error when the quadrature and the Hilbert Transform do not agree. Motivation for this method is that straightforward application of the Hilbert Transform followed by taking the derivative of the phase-angle as the Instantaneous Frequency (IF) leads to a common mistake made up to this date. In order to make the Hilbert Transform method work, the data has to obey certain restrictions.

6990436, Jan 24, 2006

Nov 28, 2003

10/729579

Norden E. Huang - Bethesda MD, US

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

G06F 15/00

702199, 702 75, 702 76

This invention presents a method for computing Instantaneous Frequency by applying Empirical Mode Decomposition to a signal and using Generalized Zero-Crossing (GZC) and Extrema Sifting. The GZC approach is the most direct, local, and also the most accurate in the mean. Furthermore, this approach will also give a statistical measure of the scattering of the frequency value. For most practical applications, this mean frequency localized down to quarter of a wave period is already a well-accepted result. As this method physically measures the period, or part of it, the values obtained can serve as the best local mean over the period to which it applies. Through Extrema Sifting, instead of the cubic spline fitting, this invention constructs the upper envelope and the lower envelope by connecting local maxima points and local minima points of the signal with straight lines, respectively, when extracting a collection of Intrinsic Mode Functions (IMFs) from a signal under consideration.

7346461, Mar 18, 2008

Sep 30, 2005

11/251004

Norden E. Huang - Bethesda MD, US
Liming W. Salvino - Rockville MD, US

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

G06F 19/00
G01H 17/00

702 56, 73570

An apparatus, computer program product and method of analyzing structures. Intrinsic Mode Functions (IMFs) are extracted from the data and the most energetic IMF is selected. A spline is fit to the envelope for the selected IMF. The spline derivative is determined. A stability spectrum is developed by separating the positive and negative results into two different spectra representing stable (positive) and unstable (negative) damping factors. The stability spectrum and the non-linearity indicator are applied to the data to isolate unstable vibrations.

7464006, Dec 9, 2008

Oct 7, 2004

10/963470

Norden E. Huang - Bethesda MD, US

The United States of America as represented by the Administrator of the National Aeronautics and Space Administration - Washington DC

G06F 15/00
H04B 15/00

702190

An apparatus, computer program product and method of analyzing non-stationary time varying phenomena. A representation of a non-stationary time varying phenomenon is recursively sifted using Empirical Mode Decomposition (EMD) to extract intrinsic mode functions (IMFs). The representation is filtered to extract intrinsic trends by combining a number of IMFs. The intrinsic trend is inherent in the data and identifies an IMF indicating the variability of the phenomena. The trend also may be used to detrend the data.