Presentation on theme: "Norden E. Huang Research Center for Adaptive Data Analysis"— Presentation transcript:
1 An Introduction to HHT: Instantaneous Frequency, Trend, Degree of Nonlinearity and Non-stationarity Norden E. HuangResearch Center for Adaptive Data AnalysisCenter for Dynamical Biomarkers and Translational MedicineNCU, Zhongli, Taiwan, China
2 Outline Rather than the implementation details, I will talk about the physics of the method. What is frequency?How to quantify the degree of nonlinearity?How to define and determine trend?
3 What is frequency? It seems to be trivial. But frequency is an important parameter for us to understand many physical phenomena.
4 Definition of Frequency Given the period of a wave as T ; the frequency is defined as
6 Other Definitions of Frequency : For any data from linear Processes
7 Definition of Power Spectral Density Since a signal with nonzero average power is not square integrable, the Fourier transforms do not exist in this case.Fortunately, the Wiener-Khinchin Theroem provides a simple alternative. The PSD is the Fourier transform of the auto-correlation function, R(τ), of the signal if the signal is treated as a wide-sense stationary random process:
9 Problem with Fourier Frequency Limited to linear stationary cases: same spectrum for white noise and delta function.Fourier is essentially a mean over the whole domain; therefore, information on temporal (or spatial) variations is all lost.Phase information lost in Fourier Power spectrum: many surrogate signals having the same spectrum.
10 Surrogate Signal: Non-uniqueness signal vs. Power Spectrum I. Hello
16 To utilize the phase to define Instantaneous Frequency
17 Prevailing Views on Instantaneous Frequency The term, Instantaneous Frequency, should be banished forever from the dictionary of the communication engineer.J. Shekel, 1953The uncertainty principle makes the concept of an Instantaneous Frequency impossible.K. Gröchennig, 2001
18 The Idea and the need of Instantaneous Frequency According to the classic wave theory, the wave conservation law is based on a gradually changing φ(x,t) such thatTherefore, both wave number and frequency must have instantaneous values and differentiable.
62 Properties of EMD Basis The Adaptive Basis based on and derived from the data by the empirical method satisfy nearly all the traditional requirements for basis empirically and a posteriori:CompleteConvergentOrthogonalUnique
63 The combination of Hilbert Spectral Analysis and Empirical Mode Decomposition has been designated by NASA asHHT(HHT vs. FFT)
74 To quantify nonlinearity we also need instantaneous frequency. AdditionallyTo quantify nonlinearity we also need instantaneous frequency.
75 How to define Nonlinearity? How to quantify it through data alone (model independent)?
76 The term, ‘Nonlinearity,’ has been loosely used, most of the time, simply as a fig leaf to cover our ignorance.Can we be more precise?
77 How is nonlinearity defined? Based on Linear Algebra: nonlinearity is defined based on input vs. output.But in reality, such an approach is not practical: natural system are not clearly defined; inputs and out puts are hard to ascertain and quantify. Furthermore, without the governing equations, the order of nonlinearity is not known.In the autonomous systems the results could depend on initial conditions rather than the magnitude of the ‘inputs.’The small parameter criteria could be misleading: sometimes, the smaller the parameter, the more nonlinear.
78 Linear SystemsLinear systems satisfy the properties of superposition and scaling. Given two valid inputs to a system H,as well as their respective outputsthen a linear system, H, must satisfyfor any scalar values α and β.
79 How is nonlinearity defined? Based on Linear Algebra: nonlinearity is defined based on input vs. output.But in reality, such an approach is not practical: natural system are not clearly defined; inputs and out puts are hard to ascertain and quantify. Furthermore, without the governing equations, the order of nonlinearity is not known.In the autonomous systems the results could depend on initial conditions rather than the magnitude of the ‘inputs.’The small parameter criteria could be misleading: sometimes, the smaller the parameter, the more nonlinear.
80 How should nonlinearity be defined? The alternative is to define nonlinearity based on data characteristics: Intra-wave frequency modulation.Intra-wave frequency modulation is known as the harmonic distortion of the wave forms. But it could be better measured through the deviation of the instantaneous frequency from the mean frequency (based on the zero crossing period).
81 Characteristics of Data from Nonlinear Processes
91 Degree of Nonlinearity DN is determined by the combination of δη precisely with Hilbert Spectral Analysis. Either of them equals zero means linearity.We can determine δ and η separately:η can be determined from the instantaneous frequency modulations relative to the mean frequency.δ can be determined from DN with known η.NB: from any IMF, the value of δη cannot be greater than 1.The combination of δ and η gives us not only the Degree of Nonlinearity, but also some indications of the basic properties of the controlling Differential Equation, the Order of Nonlinearity.
95 Lorenz ModelLorenz is highly nonlinear; it is the model equation that initiated chaotic studies.Again it has three parameters. We decided to fix two and varying only one.There is no small perturbation parameter.We will present the results for ρ=28, the classic chaotic case.
99 Comparisons Fourier Wavelet Hilbert Basis a priori Adaptive Frequency Integral transform: GlobalIntegral transform: RegionalDifferentiation:LocalPresentationEnergy-frequencyEnergy-time-frequencyNonlinearnoyes, quantifyingNon-stationaryyesYes, quantifyingUncertaintyHarmonics
100 How to define and determine Trend ? Parametric or Non-parametric?Intrinsic vs. extrinsic approach?
101 The State-of-the arts: Trend “One economist’s trend is another economist’s cycle” Watson : Engle, R. F. and Granger, C. W. J Long-run Economic Relationships. Cambridge University Press.
102 Philosophical Problem Anticipated 名不正則言不順言不順則事不成 ——孔夫子
103 Definition of the Trend Proceeding Royal Society of London, 1998 Proceedings of National Academy of Science, 2007Within the given data span, the trend is an intrinsically fitted monotonic function, or a function in which there can be at most one extremum.The trend should be an intrinsic and local property of the data; it is determined by the same mechanisms that generate the data.Being local, it has to associate with a local length scale, and be valid only within that length span, and be part of a full wave length.The method determining the trend should be intrinsic. Being intrinsic, the method for defining the trend has to be adaptive.All traditional trend determination methods are extrinsic.
104 Algorithm for TrendTrend should be defined neither parametrically nor non-parametrically.It should be the residual obtained by removing cycles of all time scales from the data intrinsically.Through EMD.
105 Global Temperature Anomaly Annual Data from 1856 to 2003
111 Comparison between non-linear rate with multi-rate of IPCC Blue shadow and blue line are the warming rate of non-linear trend.Magenta shadow and magenta line are the rate of combination of non-linear trend and AMO-like components.Dashed lines are IPCC rates.
112 ConclusionWith HHT, we can define the true instantaneous frequency and extract trend from any data.We can quantify the degree of nonlinearity. Among the applications, the degree of nonlinearity could be used to set an objective criterion in biomedical and structural health monitoring, and to quantify the degree of nonlinearity in natural phenomena.We can also determine the trend, which could be used in financial as well as natural sciences.These are all possible because of adaptive data analysis method.
113 History of HHT1998: The Empirical Mode Decomposition Method and the Hilbert Spectrum for Non-stationary Time Series Analysis, Proc. Roy. Soc. London, A454, The invention of the basic method of EMD, and Hilbert transform for determining the Instantaneous Frequency and energy.1999: A New View of Nonlinear Water Waves – The Hilbert Spectrum, Ann. Rev. Fluid Mech. 31,Introduction of the intermittence in decomposition.2003: A confidence Limit for the Empirical mode decomposition and the Hilbert spectral analysis, Proc. of Roy. Soc. London, A459,Establishment of a confidence limit without the ergodic assumption.2004: A Study of the Characteristics of White Noise Using the Empirical Mode Decomposition Method, Proc. Roy. Soc. London, A460,Defined statistical significance and predictability.
114 Recent Developments in HHT 2007: On the trend, detrending, and variability of nonlinear and nonstationary time series. Proc. Natl. Acad. Sci., 104, 14,889-14,894.2009: On Ensemble Empirical Mode Decomposition. Adv. Adaptive data Anal., 1, 1-412009: On instantaneous Frequency. Adv. Adaptive Data Anal., 2,2010: The Time-Dependent Intrinsic Correlation Based on the Empirical Mode Decomposition. Adv. Adaptive Data Anal.,2010: Multi-Dimensional Ensemble Empirical Mode Decomposition. Adv. Adaptive Data Anal., 3,2011: Degree of Nonlinearity. (Patent and Paper)2012: Data-Driven Time-Frequency Analysis (Applied and Computational Harmonic Analysis, T. Hou and Z. Shi)
115 Current Efforts and Applications Non-destructive Evaluation for Structural Health Monitoring(DOT, NSWC, DFRC/NASA, KSC/NASA Shuttle, THSR)Vibration, speech, and acoustic signal analyses(FBI, and DARPA)Earthquake Engineering(DOT)Bio-medical applications(Harvard, Johns Hopkins, UCSD, NIH, NTU, VHT, AS)Climate changes(NASA Goddard, NOAA, CCSP)Cosmological Gravity Wave(NASA Goddard)Financial market data analysis(NCU)Theoretical foundations(Princeton University and Caltech)
116 Outstanding Mathematical Problems Mathematic rigor on everything we do. (tighten the definitions of IMF,….)Adaptive data analysis (no a priori basis methodology in general)3. Prediction problem for nonstationary processes(end effects)4. Optimization problem (the best stoppage criterion and the unique decomposition ….)5. Convergence problem (finite step of sifting, best spline implement, …)
118 Do mathematical results make physical sense? Good math, yes; Bad math ,no.
119 The Job of a ScientistThe job of a scientist is to listen carefully to nature, not to tell nature how to behave.Richard FeynmanTo listen is to use adaptive method and let the data sing, and not to force the data to fit preconceived modes.
120 All these results depends on adaptive approach. Thanks