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  <title><![CDATA[Ph.D. Dissertation Defense - Tzu-Han Wang]]></title>
  <body><![CDATA[<p><strong>Title</strong><em>:&nbsp; High-resolution Wide-band Hybrid Analog-digital Converter with Reduced Peripheral Circuit Complexity</em></p><p><strong>Committee:</strong></p><p>Dr.&nbsp;Shaolan Li, ECE, Chair, Advisor</p><p>Dr.&nbsp;Visvesh Sathe, ECE</p><p>Dr.&nbsp;Saibal Mukhopadhyay, ECE</p><p>Dr.&nbsp;Jane Gu, ECE</p><p>Dr.&nbsp;Levent Degertekin, ME</p>]]></body>
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      <value><![CDATA[High-resolution Wide-band Hybrid Analog-digital Converter with Reduced Peripheral Circuit Complexity ]]></value>
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      <value><![CDATA[<p>This dissertation presents a series of energy-efficient noise-shaping data converters that improve the performance, robustness, and integration of analog-to-digital interfaces. The proposed techniques address three major challenges in SAR ADCs—limited input driving capability, kT/C noise accumulation, and sensitivity to process, voltage, and temperature (PVT) variation. A third-order hybrid EF-CIFF SAR ADC achieves stable high-order noise shaping using a single dynamic amplifier with sampling noise cancellation. A fourth-order FIA-assisted EF-CRFF design integrates a noise-suppressed buffer-in-loop and kT/C noise cancellation for robust low-OSR operation. Finally, a two-step incremental ADC (IADC) with an inter-stage sub-ranging and GENS technique attains high resolution and energy efficiency with relaxed driver requirements. Together, these architectures establish a unified framework for high-order noise-shaping SAR-based converters, enabling compact, low-power, and PVT-robust analog front ends for next-generation sensing and edge-AI applications.</p>]]></value>
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      <value><![CDATA[2025-10-24T13:00:00-04:00]]></value>
      <value2><![CDATA[2025-10-24T15:00:00-04:00]]></value2>
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      <timezone><![CDATA[America/New_York]]></timezone>
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      <value><![CDATA[Room W218, Van Leer]]></value>
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          <item><![CDATA[ECE Ph.D. Dissertation Defenses]]></item>
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