Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization
Time-varying digital filters are widely used in dynamic signal processing applications, but their transient response can significantly impact performance, particularly in real-time systems. This study focuses on reducing transient time in time-varying filters through second-order section (SOS) optim...
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MDPI AG
2025-06-01
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| Online Access: | https://www.mdpi.com/2076-3417/15/12/6512 |
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| author | Piotr Okoniewski Jacek Piskorowski |
| author_facet | Piotr Okoniewski Jacek Piskorowski |
| author_sort | Piotr Okoniewski |
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| description | Time-varying digital filters are widely used in dynamic signal processing applications, but their transient response can significantly impact performance, particularly in real-time systems. This study focuses on reducing transient time in time-varying filters through second-order section (SOS) optimization. By employing a numerical optimization approach, we selectively adjust the coefficients of a single SOS within a higher-order filter to minimize the transient period while maintaining overall stability. Using a sequential quadratic programming (SQP) algorithm, we determine a time-varying coefficient trajectory over a finite horizon, ensuring a rapid convergence to steady-state behavior. Experimental results demonstrate that this targeted coefficient adaptation reduces transient time by up to 80% compared to conventional static designs, with minimal computational overhead. Additionally, a comparative analysis with traditional linear time-invariant (LTI) filters highlights the advantage of this method in suppressing transient oscillations while preserving long-term filter characteristics. The proposed approach provides a practical and efficient strategy for enhancing filter responsiveness in applications requiring both stability and real-time adaptability. These findings suggest that selective time variation in SOS decomposition can be a valuable tool in digital filter design, improving efficiency without excessive memory or processing demands. |
| format | Article |
| id | doaj-art-107e6b77c9664520a65df609be47d5e2 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj-art-107e6b77c9664520a65df609be47d5e22025-08-20T02:24:35ZengMDPI AGApplied Sciences2076-34172025-06-011512651210.3390/app15126512Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section OptimizationPiotr Okoniewski0Jacek Piskorowski1Faculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, PolandFaculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, PolandTime-varying digital filters are widely used in dynamic signal processing applications, but their transient response can significantly impact performance, particularly in real-time systems. This study focuses on reducing transient time in time-varying filters through second-order section (SOS) optimization. By employing a numerical optimization approach, we selectively adjust the coefficients of a single SOS within a higher-order filter to minimize the transient period while maintaining overall stability. Using a sequential quadratic programming (SQP) algorithm, we determine a time-varying coefficient trajectory over a finite horizon, ensuring a rapid convergence to steady-state behavior. Experimental results demonstrate that this targeted coefficient adaptation reduces transient time by up to 80% compared to conventional static designs, with minimal computational overhead. Additionally, a comparative analysis with traditional linear time-invariant (LTI) filters highlights the advantage of this method in suppressing transient oscillations while preserving long-term filter characteristics. The proposed approach provides a practical and efficient strategy for enhancing filter responsiveness in applications requiring both stability and real-time adaptability. These findings suggest that selective time variation in SOS decomposition can be a valuable tool in digital filter design, improving efficiency without excessive memory or processing demands.https://www.mdpi.com/2076-3417/15/12/6512time-varying systemsdigital filterssecond-order section |
| spellingShingle | Piotr Okoniewski Jacek Piskorowski Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization Applied Sciences time-varying systems digital filters second-order section |
| title | Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization |
| title_full | Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization |
| title_fullStr | Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization |
| title_full_unstemmed | Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization |
| title_short | Transient Time Reduction in Time-Varying Digital Filters via Second-Order Section Optimization |
| title_sort | transient time reduction in time varying digital filters via second order section optimization |
| topic | time-varying systems digital filters second-order section |
| url | https://www.mdpi.com/2076-3417/15/12/6512 |
| work_keys_str_mv | AT piotrokoniewski transienttimereductionintimevaryingdigitalfiltersviasecondordersectionoptimization AT jacekpiskorowski transienttimereductionintimevaryingdigitalfiltersviasecondordersectionoptimization |