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TobiasWooldridge
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dsp-filter-designer

Designs IIR filters and exports Python code for WaveCap-SDR DSP pipeline.

1|Updated Oct 25, 2025
Search Tags:#design#visualization#signal processing#audio#dsp#filter#sdr
One-click install
npx skills add https://github.com/TobiasWooldridge/WaveCap-SDR --skill dsp-filter-designer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dsp-filter-designer
Source: https://github.com/TobiasWooldridge/WaveCap-SDR/tree/main/.claude/skills/dsp-filter-designer
Command: npx skills add https://github.com/TobiasWooldridge/WaveCap-SDR --skill dsp-filter-designer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, matplotlib, and includes scripts (resource) components.

What problem does it solve?

Designing and tuning digital signal processing (DSP) filters for SDR can be complex, requiring an understanding of frequency response, phase, and computational trade-offs. This skill simplifies the process by providing design, visualization, and testing tools, ensuring your audio is clean and precise.

Core Features & Use Cases

  • Interactive Filter Design: Design lowpass, highpass, bandpass, and notch filters with various characteristics (Butterworth, Chebyshev, Elliptic).
  • Response Visualization: See frequency, phase, and impulse responses to understand filter behavior and fine-tune parameters.
  • Code Export: Generate ready-to-use Python code for seamless integration into the WaveCap-SDR DSP pipeline.
  • Use Case: You need to add a 15 kHz lowpass filter for FM de-emphasis. Use this skill to design a 5th-order Butterworth filter, visualize its response, and then export the Python code directly into your filters.py file.

Quick Start

Use the dsp-filter-designer skill to design a 15000 Hz lowpass filter with order 5 for a 48000 Hz sample rate, and display its frequency response.

Frequently Asked Questions about dsp-filter-designer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design a DSP filter for audio demodulation in SDR?▼

Design DSP filters by specifying filter type (lowpass, highpass, bandpass, notch), method (Butterworth, Chebyshev, Elliptic), cutoff frequency, sample rate, and order. Visualize frequency and phase responses to verify performance before exporting Python code for your demodulation pipeline.

Can I visualize filter frequency response before implementing it?▼

Yes. The tool displays frequency response, phase response, and impulse response plots so you can inspect rolloff, -3 dB point, and ripple characteristics. Adjust parameters interactively and re-visualize until the filter meets your specifications.

How do I export filter coefficients for use in WaveCap-SDR?▼

After designing and testing your filter, export ready-to-use Python code containing filter coefficients and -3 dB metrics. The generated code integrates directly into wavecapsdr/dsp/filters.py without manual translation.

What filter types and design methods does this support?▼

Supports lowpass, highpass, bandpass, and notch filters using scipy.signal IIR methods: Butterworth, Chebyshev I, Chebyshev II, and Elliptic. Specify order and ripple parameters to balance steepness against computational cost.

Do I need to understand signal processing math to use this tool?▼

No. The tool handles scipy.signal filter design internally. Provide cutoff frequency, sample rate, and order; the visualizations show whether the result meets your needs for FM, AM, or SSB demodulation without requiring DSP theory.

Can I add notch filters to remove specific interference frequencies?▼

Yes. Notch filters are supported alongside standard filter types. Design and visualize notch response to target interference, then export the coefficient data for integration into your demodulation pipeline.

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