Overview
A high-pass filter suppresses slow trends or DC offsets and keeps components above a chosen cutoff. It is often used to emphasize edges, changes, or fast oscillations.
CoreSource checked
High-Pass Filter
Attenuates low-frequency signal components while preserving rapid changes.
Quick Facts
Compact metadata for implementation and discovery.
- Category
- Signal Processing
- Difficulty
- Beginner
- Family
- Filtering
- Tier
- Core
- Status
- Verified
- Review
- Source Checked
- Sources
- 1
- Formulas
- 1
- Relationships
- 3
- Code example
- Not ready
- Visualization
- Ready
- Aliases
- HPF
Core Concepts
signal samplesfilter kernelfilteringsample windowsignal transformnoise handling
Quick facts
Complexity
Runtime and memory behavior at a glance.
Best
O(n)
Average
O(n)
Worst
O(n)
Space
O(1)
When to Use
- Use when slow variation is nuisance signal and fast variation is informative.
- Use when the cutoff can be chosen relative to the sampling rate.
When Not to Use
- Avoid when absolute level or slow trend is meaningful.
- Avoid when phase distortion around events is unacceptable.
What It Does
- Defines a cutoff between suppressed slow components and passed fast components
- Removes baseline drift or low-frequency trend
- Outputs rapid variations in the signal
Use Cases
- Removing DC offset or baseline drift
- Detecting rapid changes
- Preprocessing signals before feature extraction
Inputs
- Signal
- Cutoff frequency
Outputs
- Filtered signal
Key Formulas (1)
Simple high-pass filter
y[i] = α · (y[i − 1] + x[i] − x[i − 1])
y[i] = alpha * (y[i - 1] + x[i] - x[i - 1])Keeps faster changes while reducing slow-moving components.
Pseudocode
- 1.Choose sample rate, cutoff, and filter design
- 2.Compute coefficients or recursive update state
- 3.For each sample, update the filter
- 4.Subtract or attenuate low-frequency content according to the design
- 5.Return the high-pass output
Canonical Example
- Input
- signal = slow ramp plus small rapid pulses
- Output
- pulses emphasized while the ramp is reduced
- Explanation
- The filter suppresses low-frequency drift and preserves faster changes.
Implementation Notes
- Document startup initialization and boundary behavior.
- Check frequency response with known low and high sine inputs.
- Choose FIR or IIR design based on phase and latency requirements.
Common Pitfalls
- Cutoff frequency must be interpreted against the sample rate.
- Startup transients can look like real high-frequency events.
- Over-filtering can amplify noise or remove useful baseline context.
Interactive Mechanism Walkthrough
Iterative Convergence & State TrajectoryShow slow drift removed while sharp changes remain.
Step 1 of 5: Choose sample rate, cutoff, and filter design
detail-waveformNotes
High-pass filters are sensitive to boundary handling and startup transients.
Sources (1)
What each reference supports for this entry.
Discrete-Time Signal Processing
BookSignal-processing reference covering digital filter behavior and frequency-selective filtering.
Open sourceExplore Next
Good next jumps from the relationship graph, ranked for useful discovery.
Relationships
View full relationship pageAlternative toLow-Pass Filter
High-pass filters preserve rapid changes, while low-pass filters smooth them away.
Conceptual neighborBand-Pass Filter
Band-pass filters combine low- and high-frequency rejection.
Related Algorithms
Tags
Signal ProcessingFilteringHigh Pass