Hilbert Transform and Analytic Signals

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hilbert-transform analytic-signals envelope phase

Core Idea

The Hilbert transform H[x(t)] produces output whose spectrum is the original spectrum multiplied by –j·sgn(f). The analytic signal z(t) = x(t) + j·H[x(t)] suppresses negative frequencies, enabling instantaneous amplitude and phase extraction. Phase unwrapping recovers instantaneous frequency as dφ/dt.

Explainer

The Fourier transform you studied decomposes a real-valued signal into complex exponentials at positive and negative frequencies. For a real signal x(t), the negative-frequency components are always the complex conjugate of the positive-frequency components — they carry no additional information. The spectrum is redundant by exactly a factor of two. The Hilbert transform and the analytic signal construction exploit this redundancy: by suppressing the negative-frequency half of the spectrum, you pack exactly the same information into a one-sided spectrum, which enables something powerful — the clean separation of a signal's instantaneous amplitude from its instantaneous phase.

The Hilbert transform H[x(t)] is defined in the frequency domain as multiplication by −j·sgn(f): positive frequencies are multiplied by −j (a 90° phase lag) and negative frequencies by +j (a 90° phase lead). In the time domain, this corresponds to convolution with 1/(πt). The output x̂(t) = H[x(t)] is a real signal that looks like x(t) with every frequency component shifted 90° in phase — the Hilbert transform of cos(2πft) is sin(2πft), and the Hilbert transform of sin(2πft) is −cos(2πft). The analytic signal is then z(t) = x(t) + j·x̂(t). By construction, its Fourier transform Z(f) is zero for f < 0 — the imaginary part exactly cancels the negative-frequency components and doubles the positive-frequency ones.

This one-sided spectrum enables envelope and phase extraction without ambiguity. Writing z(t) = A(t)·e^{jφ(t)}, the instantaneous amplitude (envelope) is A(t) = |z(t)| = √[x(t)² + x̂(t)²], and the instantaneous phase is φ(t) = arctan[x̂(t)/x(t)]. For an AM radio signal x(t) = m(t)·cos(2πf_ct), where m(t) is the message, the analytic signal gives A(t) = m(t) directly — equivalent to an ideal envelope detector. For an FM signal where frequency varies with the message, the instantaneous frequency is the time derivative of phase: f_i(t) = (1/2π)·dφ/dt.

Phase is accumulated continuously, but the arctan function wraps at ±π. Phase unwrapping adds or subtracts 2π at each discontinuity to reconstruct the smooth, continuously increasing phase that differentiates cleanly to give instantaneous frequency. This combination — analytic signal formation, envelope extraction, and phase unwrapping — is the foundation of modern demodulation algorithms, vibration analysis, and medical signal processing wherever the instantaneous properties of a real signal need to be tracked over time.

Practice Questions 5 questions

Prerequisite Chain

Counting to 10Counting to 20Understanding ZeroThe Number ZeroCounting to FiveOne-to-One CorrespondenceCombining Small Groups Within 5Addition Within 10Addition Within 20Two-Digit Addition Without RegroupingTwo-Digit Addition with RegroupingAddition Within 100Repeated Addition as MultiplicationMultiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Two-Digit by One-Digit DivisionDivision with RemaindersRemainders and Quotients in DivisionDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineOpposites and Additive InversesAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersDividing IntegersUnit RatesProportionsPercent ConceptConverting Between Fractions, Decimals, and PercentsOperations with Rational NumbersTwo-Step EquationsSolving Multi-Step EquationsEquations with Variables on Both SidesAngle Pairs: Complementary, Supplementary, and VerticalParallel Lines and TransversalsCorresponding AnglesAlternate Interior AnglesTriangle Angle Sum TheoremExterior Angle TheoremTriangle Inequality TheoremSimilar Triangles: AA SimilaritySimilar Triangles: SSS and SAS SimilarityProportions in Similar TrianglesRight Triangle Trigonometry IntroductionTrigonometric Ratios ReviewRadian MeasureConverting Between Degrees and RadiansThe Unit CirclePythagorean Trigonometric IdentitiesFourier Series Representation of Periodic SignalsFourier Transform: Definition and PropertiesHilbert Transform and Analytic Signals

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