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Miha Kralj
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lib/filters/rls/Rls.md
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- The Recursive Least Squares (RLS) adaptive filter is the Rolls-Royce of adaptive FIR filters.
- Parameterized by `order` (default 16), `lambda` (default 0.99).
- Output range: Tracks input.
- Requires `order + 1` bars of warmup before first valid output (IsHot = true).
- **Similar:** [LMS](../lms/Lms.md), [Kalman](../kalman/Kalman.md) | **Complementary:** Error metrics | **Trading note:** Recursive Least Squares; faster convergence than LMS but higher computational cost. Forgetting factor adapts to regime changes.
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
## Introduction
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- Haykin, S. (2002). *Adaptive Filter Theory*. 4th ed. Prentice Hall. Chapters 9-10.
- Ljung, L. & Soderstrom, T. (1983). *Theory and Practice of Recursive Identification*. MIT Press.
- Sayed, A.H. (2008). *Adaptive Filters*. Wiley-IEEE Press.
- Kalman, R.E. (1960). "A New Approach to Linear Filtering and Prediction Problems." *Journal of Basic Engineering*, 82(1), 35-45.
- Kalman, R.E. (1960). "A New Approach to Linear Filtering and Prediction Problems." *Journal of Basic Engineering*, 82(1), 35-45.