Sharif University of Technology Scientia Iranica 1026-3098 Articles in Press 2023 10 04 Spline NLMS Adaptive Filter Algorithm based on the Signed Regressor of Input Signal 23356 10.24200/sci.2023.62258.7738 EN Hossein Tavakoli Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, P.O.Box:16785-163, Tehran, Iran Mohammad Shams Esfand Abadi Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, P.O.Box:16785-163, Tehran, Iran Journal Article 2023 04 17 This paper presents a new spline adaptive filtering (SAF) algorithm based on signed regressor (SR) of input signal. The algorithm is called SR-SAF normalized least mean squares (SR-SAF-NLMS). The SR-SAF-NLMS is established through $L_{1}$-norm constraint to the proposed cost function. In this algorithm, the polarity of the input signal is used to adjust the weight coefficients and control point vectors. Therefore, the computational complexity, especially the number of multiplications, is significantly reduced. Furthermore, the performance of the SR-SAF-NLMS is close to the conventional SAF-NLMS. The good performance of the proposed algorithm is demonstrated through several simulation results in different scenarios. https://scientiairanica.sharif.edu/article_23356_0a800ef7b7c3bf3c0678e819f4b8e16b.pdf