Arockia Twinkle J , Srinivasan R , Premanand V. Chandramani
{"title":"δ σ调制器四阶噪声传递函数的粒子群算法优化","authors":"Arockia Twinkle J , Srinivasan R , Premanand V. Chandramani","doi":"10.1016/j.vlsi.2025.102539","DOIUrl":null,"url":null,"abstract":"<div><div>Delta Sigma Modulator (ΔΣM) has in-built noise shaping feature, which is defined by Noise Transfer Function (NTF). Optimization of NTF directly improves the noise shaping property of the ΔΣM and its overall performance. The proposed method employs PSO algorithm for optimizing the NTF. By utilizing its robust global optimization abilities, the PSO algorithm efficiently navigates the design space, converging on optimal NTF that yields Signal to Quantization Noise (SQNR) of 62.7244 dB. Additionally, Cascade of Resonators with Feed-Forward (CRFF) <span><math><mrow><mo>Δ</mo><mi>Σ</mi></mrow></math></span>M synthesized with the proposed NTF achieves peak-to-peak SNR (<span><math><mrow><msub><mtext>SNR</mtext><mrow><mi>p</mi><mn>2</mn><mi>p</mi></mrow></msub></mrow></math></span>)/peak signal-to-noise ratio (Peak SNR)/average SNR (Peak SNR) of 92.5 dB/82.9594 dB/82.1 dB with reduced computational complexity. The proposed method achieves higher SQNR × Over load level for different Oversampling Ratio (OSR) values when compared to the existing methods.</div></div>","PeriodicalId":54973,"journal":{"name":"Integration-The Vlsi Journal","volume":"106 ","pages":"Article 102539"},"PeriodicalIF":2.5000,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of fourth order noise transfer function using PSO algorithm for delta sigma modulator\",\"authors\":\"Arockia Twinkle J , Srinivasan R , Premanand V. Chandramani\",\"doi\":\"10.1016/j.vlsi.2025.102539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Delta Sigma Modulator (ΔΣM) has in-built noise shaping feature, which is defined by Noise Transfer Function (NTF). Optimization of NTF directly improves the noise shaping property of the ΔΣM and its overall performance. The proposed method employs PSO algorithm for optimizing the NTF. By utilizing its robust global optimization abilities, the PSO algorithm efficiently navigates the design space, converging on optimal NTF that yields Signal to Quantization Noise (SQNR) of 62.7244 dB. Additionally, Cascade of Resonators with Feed-Forward (CRFF) <span><math><mrow><mo>Δ</mo><mi>Σ</mi></mrow></math></span>M synthesized with the proposed NTF achieves peak-to-peak SNR (<span><math><mrow><msub><mtext>SNR</mtext><mrow><mi>p</mi><mn>2</mn><mi>p</mi></mrow></msub></mrow></math></span>)/peak signal-to-noise ratio (Peak SNR)/average SNR (Peak SNR) of 92.5 dB/82.9594 dB/82.1 dB with reduced computational complexity. The proposed method achieves higher SQNR × Over load level for different Oversampling Ratio (OSR) values when compared to the existing methods.</div></div>\",\"PeriodicalId\":54973,\"journal\":{\"name\":\"Integration-The Vlsi Journal\",\"volume\":\"106 \",\"pages\":\"Article 102539\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Integration-The Vlsi Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167926025001968\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integration-The Vlsi Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167926025001968","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Optimization of fourth order noise transfer function using PSO algorithm for delta sigma modulator
Delta Sigma Modulator (ΔΣM) has in-built noise shaping feature, which is defined by Noise Transfer Function (NTF). Optimization of NTF directly improves the noise shaping property of the ΔΣM and its overall performance. The proposed method employs PSO algorithm for optimizing the NTF. By utilizing its robust global optimization abilities, the PSO algorithm efficiently navigates the design space, converging on optimal NTF that yields Signal to Quantization Noise (SQNR) of 62.7244 dB. Additionally, Cascade of Resonators with Feed-Forward (CRFF) M synthesized with the proposed NTF achieves peak-to-peak SNR ()/peak signal-to-noise ratio (Peak SNR)/average SNR (Peak SNR) of 92.5 dB/82.9594 dB/82.1 dB with reduced computational complexity. The proposed method achieves higher SQNR × Over load level for different Oversampling Ratio (OSR) values when compared to the existing methods.
期刊介绍:
Integration''s aim is to cover every aspect of the VLSI area, with an emphasis on cross-fertilization between various fields of science, and the design, verification, test and applications of integrated circuits and systems, as well as closely related topics in process and device technologies. Individual issues will feature peer-reviewed tutorials and articles as well as reviews of recent publications. The intended coverage of the journal can be assessed by examining the following (non-exclusive) list of topics:
Specification methods and languages; Analog/Digital Integrated Circuits and Systems; VLSI architectures; Algorithms, methods and tools for modeling, simulation, synthesis and verification of integrated circuits and systems of any complexity; Embedded systems; High-level synthesis for VLSI systems; Logic synthesis and finite automata; Testing, design-for-test and test generation algorithms; Physical design; Formal verification; Algorithms implemented in VLSI systems; Systems engineering; Heterogeneous systems.