SEI-ADE
所属分类：模式识别(视觉/语音等)
开发工具：Python
文件大小：0KB
下载次数：1
上传日期：2023-08-25 10:13:06
上 传 者：
sh-1993
说明： 用于特定辐射源识别的单个指纹特征的自适应分解和提取网络，
(Adaptive Decomposition and Extraction Network of Individual Fingerprint Features for Specific Emitter Identification,)
文件列表:
LICENSE (1066, 2023-08-25)
environment.yml (582, 2023-08-25)
finger_feature_images/ (0, 2023-08-25)
finger_feature_images/S_9001_00003_00001 (2).jpg (41940, 2023-08-25)
finger_feature_images/S_9001_00003_00001 signals decomposed by DNet.png (21375, 2023-08-25)
finger_feature_images/S_9001_00003_00001 spectrum of the individual signal.png (13222, 2023-08-25)
finger_feature_images/S_9001_00003_00001.jpg (35760, 2023-08-25)
main.py (8261, 2023-08-25)
module/ (0, 2023-08-25)
module/0.get_datum.sh (50, 2023-08-25)
module/__init__.py (0, 2023-08-25)
module/__pycache__/ (0, 2023-08-25)
module/__pycache__/__init__.cpython-35.pyc (167, 2023-08-25)
module/__pycache__/__init__.cpython-36.pyc (141, 2023-08-25)
module/__pycache__/__init__.cpython-37.pyc (183, 2023-08-25)
module/__pycache__/__init__.cpython-38.pyc (178, 2023-08-25)
module/__pycache__/dataset.cpython-36.pyc (8314, 2023-08-25)
module/__pycache__/dataset_bht.cpython-36.pyc (7692, 2023-08-25)
module/__pycache__/datum_pb2.cpython-36.pyc (2275, 2023-08-25)
module/__pycache__/executor.cpython-36.pyc (12501, 2023-08-25)
module/__pycache__/sampler.cpython-36.pyc (5777, 2023-08-25)
module/__pycache__/triplet_loss.cpython-36.pyc (3170, 2023-08-25)
module/__pycache__/utils.cpython-35.pyc (16939, 2023-08-25)
module/__pycache__/utils.cpython-36.pyc (15499, 2023-08-25)
module/__pycache__/utils.cpython-37.pyc (15528, 2023-08-25)
module/__pycache__/utils.cpython-38.pyc (15316, 2023-08-25)
module/dataset.py (12302, 2023-08-25)
module/datum.proto (292, 2023-08-25)
module/datum_pb2.py (3972, 2023-08-25)
module/executor.py (20352, 2023-08-25)
module/executor_test.py (22371, 2023-08-25)
module/protoc/ (0, 2023-08-25)
module/protoc/bin/ (0, 2023-08-25)
module/protoc/bin/protoc (4396888, 2023-08-25)
module/protoc/include/ (0, 2023-08-25)
module/protoc/include/google/ (0, 2023-08-25)
module/protoc/include/google/protobuf/ (0, 2023-08-25)
module/protoc/include/google/protobuf/any.proto (5483, 2023-08-25)
module/protoc/include/google/protobuf/api.proto (7734, 2023-08-25)
... ...
## Adaptive Decomposition and Extraction Network of Individual Fingerprint Features for Specific Emitter Identification
## Overview
This project implemented SEI-ADE for Specific Emitter Identification and tested on multiple types of electromagnetic datasets.
### Training datasets and test datasets
Relevant training data sets and test data sets will be released in the near future.
The dataset for the demonstration is placed on Baidu's website: https://pan.baidu.com/s/1qXTtAGy3jV1KjgqnuTfbBA?pwd=zjnc
### Example Output
> * The Mark map, Waveform and spectrum of 2-channel signals decomposed by DNet
### Best Model
> *Our trained model is placed on Baidu's website: https://pan.baidu.com/s/1DxwBkp8oNU-EzR_zrLRrzg?pwd=zjnc
This repository was developed and tested in PyTorch 1.5.
## How to run
- Intall required dependencies as listed in [environment.yml](https://github.com/jn-z/SEI-ADE/blob/master/./environment.yml)
- Run [run_train_spk.sh] for training and [run_test.sh] for testing
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