Philip H. W. Leong

发表

International Conference on Field Programmable Logic and Applications, FPL 2010, August 31 2010 - September 2, 2010, Milano, Italy

Philip H. W. Leong, Andreas Koch, Eduardo Boemo, 2010, FPL.

An FPGA-Based Floating Point Unit for Rounding Error Analysis

Philip H. W. Leong, Michael Frechtling, P. Leong, 2015 .

Development ofaHumanAirbagSystemforFallProtection UsingMEMS MotionSensing Technology

Philip H. W. Leong, Guangyi Shi, Guanglie Zhang, 2006 .

Proceedings of the 2005 International Conference on Field Programmable Logic and Applications (FPL), Tampere, Finland, August 24-26, 2005

Steven J. E. Wilton, Philip H. W. Leong, Tero Rissa, 2005, FPL.

Floating Point FPGAs

Wayne Luk, Philip H. W. Leong, Chi Wai Yu, 2008 .

An assembly language for efficient physical-layer classical control in quantum processors

Michael J. Biercuk, Philip H. W. Leong, Harrison Ball, 2016 .

Keynote speech: FPGA-based machine learning for prognostics and system health management

Philip H. W. Leong, 2017 .

SMCGen: Generating Reconfigurable Design for Sequential Monte Carlo Applications

Wayne Luk, James Stanley Targett, Peter Y. K. Cheung, 2014, FCCM 2014.

Residential battery sizing model using net meter energy data clustering

Philip H. W. Leong, Rui Tang, Baran Yildiz, 2019, Applied Energy.

Kakadu — a micropower neural network

Philip H. W. Leong, 1996 .

FPGA implementation of biologically-inspired auto-associative memory

Philip H. W. Leong, Craig Jin, Alistair McEwan, 2012 .

Digital Signal Processing for the Auditory Scientist: A Tutorial Introduction

Philip H. W. Leong, Simon Carlile, Tim Tucker, 1996 .

Non-volatile programmable pulse computation cell

Philip H. W. Leong, Craig Jin, Pier Luigi Rolandi, 1999 .

Vision Guided Crop Detection in Field Robots using FPGA-Based Reconfigurable Computers

Hayden Kwok-Hay So, Philip H. W. Leong, Cyrus Wing-Hei Chan, 2020, ISCAS.

Monte Carlo Deep Neural Network Arithmetic

Philip H. W. Leong, Julian Faraone, P. Leong, 2019 .

A VLSI neural network for morphology classification

Philip H. W. Leong, M. A. Jabri, 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

Nonlinear retinal response modeling for future neuromorphic instrumentation

Derek Abbott, Omid Kavehei, Said Al-Sarawi, 2020, IEEE Instrumentation & Measurement Magazine.

THE COARSE-GRAINED/FINE-GRAINEDLOGICINTERFACEINFPGASWITH EMBEDDED FLOATING-POINTARITHMETICUNITS

Philip H. W. Leong, Julien Lamoureux, Steven Je . Wilton, 2008 .

ANN Based Classification for Heart Defibrillators

Philip H. W. Leong, Barry Flower, S. Pickard, 1991, NIPS 1991.

VLSI implementation of neural networks with application to signal processing

Philip H. W. Leong, Marwan A. Jabri, Barry Flower, 1991, 1991., IEEE International Sympoisum on Circuits and Systems.

A Comment on the Implementation of the Ziggurat Method

Wayne Luk, Philip H. W. Leong, John Villasenor, 2005 .

Prediction of High-Dimensional Time Series with Exogenous Variables Using Generalized Koopman Operator Framework in Reproducing Kernel Hilbert Space

Philip H. W. Leong, Gemunu H. Gunaratne, Jorge Goncalves, 2017 .

International Conference on Field Programmable Logic and Applications, FPL 2011, September 5-7, Chania, Crete, Greece

Philip H. W. Leong, Andreas Koch, Eduardo Boemo, 2011, FPL.

Convolutional Neural Networks for Subgure Classication

Philip H. W. Leong, Ashnil Kumar, Dagan Feng, 2015 .

Kernel Normalised Least Mean Squares with Delayed Model Adaptation

Philip H. W. Leong, Nicholas J. Fraser, P. Leong, 2020, ACM Trans. Reconfigurable Technol. Syst..

The Coarse-Grained / Fine-Grained Logic Interface in FPGAs with Embedded Floating-Point Arithmetic Units

Wayne Luk, Steven J. E. Wilton, Philip H. W. Leong, 2008 .

Application of Grammar Framework to Time-Series Prediction

Philip H. W. Leong, Anthony Mihirana De Silva, 2015 .

High-dimensional time series prediction using kernel-based Koopman mode regression

Philip H. W. Leong, Gemunu H. Gunaratne, Duncan J. M. Moss, 2017, Nonlinear Dynamics.

RNA: An Accurate Residual Network Accelerator for Quantized and Reconstructed Deep Neural Networks

Wei Cao, Lingli Wang, Philip H. W. Leong, 2019, IEICE Transactions on Information and Systems.

MSL16A: an asynchronous Forth microprocessor

Philip H. W. Leong, K. H. Leung, P. K. Tsang, 1999, Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030).

Grammar-Based Feature Generation for Time-Series Prediction

Philip H. W. Leong, Anthony Mihirana De Silva, P. Leong, 2015 .

Grammar Based Feature Generation

Philip H. W. Leong, Anthony Mihirana De Silva, P. Leong, 2015 .

AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers

Peter Zipf, Martin Kumm, Philip H. W. Leong, 2019, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

gramEvol: Grammatical Evolution in R

Philip H. W. Leong, Farzad Noorian, Anthony Mihirana De Silva, 2016 .

Interpolating high granularity solar generation and load consumption data using super resolution generative adversarial network

Rui Tang, Philip H. W. Leong, Jonathon Dore, 2021 .

Integrated silicon nitride time-bin entanglement circuits

Philip H. W. Leong, Benjamin J. Eggleton, Chunle Xiong, 2018, CLEO 2018.

Stochastic Receding Horizon Control for Short-Term Risk Management in Foreign Exchange

Philip H. W. Leong, Philip H. W. Leong, Barry Flower, 2015 .

FPGA based runtime configurable clause evaluator for SAT problems

Philip H. W. Leong, C. K. Chung, 1999 .