# IEEE Signal Processing Letters

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/ieee-signal-processing-letters/

## Facts

| Field | Value |
| --- | --- |
| Open Access | false |
| ISSN-L | 1070-9908 |
| ISSNs | 1070-9908,1558-2361 |
| OpenAlex ID | https://openalex.org/S120629676 |
| Publisher | Institute of Electrical and Electronics Engineers |

## Journal papers

- [SkeletonNet: Mining Deep Part Features for 3-D Action Recognition](https://scholariq.org/papers/skeletonnet-mining-deep-part-features-for-3-d-action-recognition/)
- [Low-complexity lossless compression of hyperspectral imagery via linear prediction](https://scholariq.org/papers/low-complexity-lossless-compression-of-hyperspectral-imagery-via-linear/)
- [MRI and SPECT Image Fusion Using a Weighted Parameter Adaptive Dual Channel PCNN](https://scholariq.org/papers/mri-and-spect-image-fusion-using-a-weighted-parameter-adaptive-dual-channel-pcnn/)
- [Detection of Moving Objects Using Fuzzy Color Difference Histogram Based Background Subtraction](https://scholariq.org/papers/detection-of-moving-objects-using-fuzzy-color-difference-histogram-based/)
- [A 1.5-D Multi-Channel EEG Compression Algorithm Based on NLSPIHT](https://scholariq.org/papers/a-1-5-d-multi-channel-eeg-compression-algorithm-based-on-nlspiht/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.