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Hilbert Transform and Analytic Signals

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Fourier Transform: Definition and Properties→→Cepstral Analysis and Homomorphic FilteringInstantaneous Amplitude and Frequency Estimation+1 more
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)·ejφ(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

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Angle Pairs: Complementary, Supplementary, and Vertical → Parallel Lines and Transversals → Corresponding Angles → Alternate Interior Angles → Triangle Angle Sum Theorem → Exterior Angle Theorem → Triangle Inequality Theorem → Similar Triangles: AA Similarity → Similar Triangles: SSS and SAS Similarity → Proportions in Similar Triangles → Right Triangle Trigonometry Introduction → Sine, Cosine, and Tangent Ratios → Trigonometric Ratios Review → Radian Measure → Converting Between Degrees and Radians → The Unit Circle → Pythagorean Trigonometric Identities → Fourier Series Representation of Periodic Signals → Fourier Transform: Definition and Properties → Hilbert Transform and Analytic Signals

Longest path: 81 steps · 355 total prerequisite topics

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