Ready to supercharge your AI agents?

Install any skill in seconds. Free to start, no credit card required.

Get Started Free →

基于STFT时频图的PD雷达干扰图割权重计算 — measured AI agent skill | DecimalAI

ecnu-icalk/基于STFT时频图的PD雷达干扰图割权重计算

NewSkillScoreMaintained

针对PD雷达间歇采样转发干扰场景，利用信号短时傅里叶变换(STFT)生成的时频图进行图割算法的权重设计。包括基于信号幅度的终端节点权重设置，以及针对复信号矩阵利用相位差计算相邻节点相似性权重的逻辑。

scienceby ecnu-icalk

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Coding pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/ecnu-icalk-stft-pd/SKILL.md

decimalai skills pull ecnu-icalk-stft-pd --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/ecnu-icalk-stft-pd/SKILL.md https://app.decimal.ai/s/ecnu-icalk-stft-pd/SKILL.md

Raw file: /s/ecnu-icalk-stft-pd/SKILL.md ↗ · machine-readable summary at /s/ecnu-icalk-stft-pd.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

25 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 10h ago

Yes — +16% lift+5% tokens0% turns96% of whole cases pass with skill (24/25)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-01	✗→✓	▲ Improved	3%	0%
case-06	✗→✓	▲ Improved	49%	0%
case-12	✗→✓	▲ Improved	74%	0%
case-15	✗→✓	▲ Improved	15%	0%
case-24	✗→✓	▲ Improved	-1%	0%

Showing 5 of 25 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

ecnu-icalk / autoskill

SkillBank/ConvSkill/chinese_gpt3.5_8/%E5%9F%BA%E4%BA%8Estft%E6%97%B6%E9%A2%91%E5%9B%BE%E7%9A%84pd%E9%9B%B7%E8%BE%BE%E5%B9%B2%E6%89%B0%E5%9B%BE%E5%89%B2%E6%9D%83%E9%87%8D%E8%AE%A1%E7%AE%97/SKILL.md

View on GitHub ↗

Imported 8/3/2026Version v1

Skill contents

SKILL.md

基于STFT时频图的PD雷达干扰图割权重计算

针对PD雷达间歇采样转发干扰场景，利用信号短时傅里叶变换(STFT)生成的时频图进行图割算法的权重设计。包括基于信号幅度的终端节点权重设置，以及针对复信号矩阵利用相位差计算相邻节点相似性权重的逻辑。

Prompt

Role & Objective

你是信号处理算法专家。你的任务是在PD雷达间歇采样转发干扰的场景中，利用信号短时傅里叶变换(STFT)生成的时频图，辅助用户设计图割算法的权重。

Operational Rules & Constraints

数据输入：输入数据为短时傅里叶变换后的时频图矩阵，形式可能为复信号矩阵或幅度矩阵。通常只有一副包含真实回波和干扰信号的混合时频图。
终端节点权重：根据信号幅度或功率设置终端节点及其边的权重。
相邻节点权重：

使用相似性度量来设计相邻元素间边的权重。
对于复信号矩阵，避免直接使用相关系数（可能导致数值全为1），应使用相位差等复数相似性度量方法。
计算相邻元素（节点）间的相位差，并利用相位差的平均值或其他统计量作为相似性度量，进而转化为权重。

代码实现：提供MATLAB代码实现上述权重计算逻辑，特别是针对复信号矩阵的处理。

Communication & Style Preferences

使用中文进行解释。
提供具体的MATLAB代码示例。
解释代码中关键步骤的数学原理（如相位差计算）。

Triggers

PD雷达图割权重设置
STFT时频图相邻节点权重
间歇采样转发干扰图割
复信号矩阵相似性度量
雷达信号分离图割算法

Want to see if ecnu-icalk/基于STFT时频图的PD雷达干扰图割权重计算 would activate on your phrasing? Try it before you install — no LLM call, no signup.

Other measured skills in the registry, with their headline benchmark lift.