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DC25_SLIDES_Track12_MultiplePulsesBasedDecisionFeedbackEqualizer_Tan.pdf

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1、Information Classification:GeneralWelcome to ConferenceJanuary 2830,2025Santa Clara Convention Center1ExpoJanuary 2930,2025Information Classification:GeneralMultiple Pulses-Based Decision Feedback Equalizer(MPDFE)for PAM4Kan Tan,(Tektronix Inc.)Muhammad Saad Chughtai,(Tektronix Inc.)Justin Patterson

2、,(Tektronix Inc.)Kan Tan,Muhammad Saad Chughtai,Justin Patterson2Information Classification:GeneralImageImage SPEAKERSKan TanPrincipal Engineer,Tektronix IKan has worked on DSP for performance scopes,signal integrity analysis,and serial data link analysis.He has applied machine learning to measureme

3、nts.He designed new instruments for wideband signal generation and analysis.He received a Ph.D.degree in Control System from University of Houston.Software Design Engineer,Tektronix Inc.M3Saad has worked on designing measurement software for the latest high-speed digital standards.He received his M.

4、S.degree in Electrical and Computer Engineering from Georgia Tech.Saads areas of expertise include digital signal processing,machine learning,jitter and noise analysis as well as GPU computing.Muhammad Saad ChughtaiInformation Classification:GeneralImageSPEAKERSJustin Patterson4DSP Software Engineer

5、,Tektronix IJustin has worked on algorithm development for signal integrity analysis and simulation.He has worked on applying data-driven methods to oscilloscope measurements.He graduated with a B.S.in Electrical Engineering from Portland State University with a focus in signal processing.Informatio

6、n Classification:General Review of the DFE based on single linear fit pulse response(LFPR).Review of the multiple linear fit pulse responses(Multiple LFPR).Introduce the MPDFE based on multiple LFPR.Compare DFE,MPDFE and MLSE.CONTENT5Information Classification:General There is a single set of DFE ta

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1. **会议信息**:2025年1月28-30日于圣克拉拉会议中心举办,1月29-30日设展览区。 2. **技术主题**:提出基于多线性拟合脉冲响应(Multiple LFPR)的MPDFE均衡器,用于PAM4信号,解决传统DFE在符号3和2上残留ISI的问题。 3. **核心对比**: - **DFE vs. MPDFE**:MPDFE眼图垂直眼开更大,符号中心轨迹更细(引用图19)。 - **计算复杂度**:MLSE(L=40)达1.2E24,远高于DFE(160)和MPDFE(80)(引用图20)。 4. **作者背景**:Tektronix团队,涵盖DSP、机器学习及信号完整性分析领域专家。
**MPDFE优势?** **DFE局限?** **MLSE对比?**
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