IEEE TSP Submission Assistant
Evaluates manuscript fit, reframes algorithms with theoretical guarantees, and optimizes submissions for IEEE Transactions on Signal Processing.
This Claude Code skill evaluates manuscript fit, theoretical rigor, and presentation standards for IEEE Transactions on Signal Processing (IEEE TSP). It helps researchers and signal processing engineers translate empirical algorithmic results into rigorous, publication-ready manuscripts with clear signal models, formal convergence/performance bounds, and matched baselines. Featuring desk-reject diagnostics, structural checklists, and venue rerouting decisions for sister IEEE journals, it streamlines the preparation process for both Regular Papers and Correspondence items.
Key Features
01Guides reframing of empirical algorithms to incorporate formal signal models, theoretical guarantees, and convergence analysis
02Evaluates manuscript alignment with IEEE Transactions on Signal Processing theoretical and methodological standards
03Identifies common desk-reject triggers like weak baseline comparisons, missing variance metrics, or generic ML framing
041,074 GitHub stars
05Delivers structured pre-submission checklists covering article types, length policies, and reproducibility standards
06Provides intelligent venue re-routing recommendations across IEEE sister journals (e.g., IEEE T-Comm, IEEE T-IT)
Use Cases
01Reframing an empirical machine learning algorithm into a model-based signal processing manuscript with theoretical guarantees
02Deciding whether a paper is best suited for IEEE TSP, IEEE T-Comm, or IEEE Transactions on Information Theory
03Assessing fit and diagnosing desk-reject risks before submitting a manuscript to IEEE Transactions on Signal Processing