# VipaiLab/Signals-and-Systems-course

浙江大学信电学院2022信号与系统课程资料

Repository: https://github.com/VipaiLab/Signals-and-Systems-course
Canonical: https://ross.abutalabs.com/products/signals-and-systems-course
Language: MATLAB
License Family: other
Last push: 2022-07-16T04:20:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1509, "days_push": 1509, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1075, forks 201 (observed 2026-08-28T04:03:29.339581+00:00)

## What it is
Course materials for Zhejiang University's 2022 Signals and Systems course, including lecture resources and MATLAB programming exercises. It accompanies a video lecture series emphasizing rigorous theory combined with practice across continuous and discrete, one- and two-dimensional signals.

## Use cases
- learn signals and systems from course materials
- find MATLAB exercises for signal processing coursework
- study continuous and discrete signal theory with practice
- self-study a university signals and systems course
- get lecture notes for signals and systems in Chinese

## When to choose
- you want a structured university course with video lectures and MATLAB practice
- you prefer rigorous theoretical derivations paired with hands-on coding
- you are studying signals and systems in Chinese

## When to avoid
- you need production signal-processing software or libraries
- you want English-language materials
- you need actively updated content or official support

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools
- domain: education, tutorials
- platform: cross-platform
- tags: signals-and-systems, matlab, course-materials, signal-processing, lecture-notes, zhejiang-university, algorithms

## Member repositories
- VipaiLab/Signals-and-Systems-course (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:29.339581+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:53:25.296473+00:00, confidence not recorded.
  - readme: https://github.com/VipaiLab/Signals-and-Systems-course (fetched 2026-08-28T04:03:29.339581+00:00, sha b329a4161274)
- Data as of 2026-08-30T08:39:29.467469+00:00.