Hoi Wong
Engr, Electrical Engineering
Stanford University
M.Sc Electrical Engineering
Stanford Univerity
B.Sc Electrical and Computer Engineering (Hons)
B.Sc Mathematics (Hons)
University of Wisconsin - Madison
Stanford University
M.Sc Electrical Engineering
Stanford Univerity
B.Sc Electrical and Computer Engineering (Hons)
B.Sc Mathematics (Hons)
University of Wisconsin - Madison
Current Technical Skills
Signal Processing & Mathematical Algorithm Development
Biomedical Devices Research and Development
Expert uses of MATLAB: complex data systems, advanced data structures, GUI, DCOM, compiler & deployment, GPU parallel programming, DAQ and instrument control, object oriented programming.
Embedded DSP Software Development: TI TMS320 (C99), ADI SHARC (C++), AVR
Analog Electronics (Signal conditioning and interfaces)
Biomedical Devices Research and Development
Expert uses of MATLAB: complex data systems, advanced data structures, GUI, DCOM, compiler & deployment, GPU parallel programming, DAQ and instrument control, object oriented programming.
Embedded DSP Software Development: TI TMS320 (C99), ADI SHARC (C++), AVR
Analog Electronics (Signal conditioning and interfaces)
Research & Publications
[Engr Thesis] Macro-Adaptive Filtering, Stanford University
By coordinating the inputs and manipulating the outputs to one or multiple adaptive filters (with different characteristics), an adaptive filter wrapper (called macro-adaptive filter) can outpermform its constituents (in terms of convergence speed, steady-state error, numerical stability, robustness to disturbances).
The thesis demonstrated a few macro-adaptive filters with simultaneously faster convergence and lower steady-state error for LMS algorithm with guaranteed numerical stability. Another macro-adaptive filter in the thesis broke the LMS algorithm's maximum learning-rate barrier (before it goes unstable). Combining the two macro-adaptive algorithms, the LMS algorithm family can be boosted to achieve low misadjustments closer to RLS while retaining the robustness and stability of LMS algorithm by design.
[Undergraduate Publication]
H. Wong and W. A. Sethares, “Estimation of Pseudo-periodic Signals”, IEEE Proceedings of International Conference on Acoustics, Speech and Signal Processing, Montreal, May 2004.
By coordinating the inputs and manipulating the outputs to one or multiple adaptive filters (with different characteristics), an adaptive filter wrapper (called macro-adaptive filter) can outpermform its constituents (in terms of convergence speed, steady-state error, numerical stability, robustness to disturbances).
The thesis demonstrated a few macro-adaptive filters with simultaneously faster convergence and lower steady-state error for LMS algorithm with guaranteed numerical stability. Another macro-adaptive filter in the thesis broke the LMS algorithm's maximum learning-rate barrier (before it goes unstable). Combining the two macro-adaptive algorithms, the LMS algorithm family can be boosted to achieve low misadjustments closer to RLS while retaining the robustness and stability of LMS algorithm by design.
[Undergraduate Publication]
H. Wong and W. A. Sethares, “Estimation of Pseudo-periodic Signals”, IEEE Proceedings of International Conference on Acoustics, Speech and Signal Processing, Montreal, May 2004.
Teaching Assistantships
Stanford University
| EE 122B | Biomedical Electronics Laboratory | |
| EE 367B Music 421 |
Applications of Fast Fourier Transform | |
| Physics 105 | Analog Electronics Laboratory | |
| BioE 200C | Medical Device, Diagnostics, and Pharmaceuticals: Technologies, Regulation and Applications |
Presentations
