Bruce F. Cockburn

Bruce F. Cockburn

University of Alberta

H-index: 28

North America-Canada

About Bruce F. Cockburn

Bruce F. Cockburn, With an exceptional h-index of 28 and a recent h-index of 14 (since 2020), a distinguished researcher at University of Alberta, specializes in the field of Computer Engineering, Testing and Verification, Parallel Computing, Communications.

His recent articles reflect a diverse array of research interests and contributions to the field:

Hardware-Efficient Logarithmic Floating-Point Multipliers for Error-Tolerant Applications

Logarithmic Floating-Point Multipliers for Efficient Neural Network Training

Fast and low‐power leading‐one detectors for energy‐efficient logarithmic computing

A logarithmic floating-point multiplier for the efficient training of neural networks

Design of an Imaging Payload for Earth Observation from a Nanosatellite

An Improved Logarithmic Multiplier for Energy-Efficient Neural Computing

Low-Power Approximate Logarithmic Squaring Circuit Design for DSP Applications

High-throughput FPGA-based Hardware Accelerators for Deflate Compression and Decompression Using High-Level Synthesis

Bruce F. Cockburn Information

University

Position

Professor

Citations(all)

2709

Citations(since 2020)

941

Cited By

2058

hIndex(all)

28

hIndex(since 2020)

14

i10Index(all)

80

i10Index(since 2020)

20

Email

University Profile Page

Google Scholar

Bruce F. Cockburn Skills & Research Interests

Computer Engineering

Testing and Verification

Parallel Computing

Communications

Top articles of Bruce F. Cockburn

Title

Journal

Author(s)

Publication Date

Hardware-Efficient Logarithmic Floating-Point Multipliers for Error-Tolerant Applications

IEEE Transactions on Circuits and Systems I: Regular Papers

Zijing Niu

Tingting Zhang

Honglan Jiang

Bruce F Cockburn

Leibo Liu

...

2023/11/2

Logarithmic Floating-Point Multipliers for Efficient Neural Network Training

Tingting Zhang

Zijing Niu

Honglan Jiang

Bruce F Cockburn

Leibo Liu

...

2023/8/17

Fast and low‐power leading‐one detectors for energy‐efficient logarithmic computing

IET Computers & Digital Techniques

Mohammad Saeed Ansari

Shyama Gandhi

Bruce F Cockburn

Jie Han

2021/7

A logarithmic floating-point multiplier for the efficient training of neural networks

Zijing Niu

Honglan Jiang

Mohammad Saeed Ansari

Bruce F Cockburn

Leibo Liu

...

2021/6/22

Design of an Imaging Payload for Earth Observation from a Nanosatellite

Elliot Saive

Liam Droog

Katelyn Ball

Jari Swanson

Elizabeth Chao

...

2021

An Improved Logarithmic Multiplier for Energy-Efficient Neural Computing

IEEE Transactions on Computers

Mohammad Saeed Ansari

Bruce F Cockburn

Jie Han

2020/5/7

Low-Power Approximate Logarithmic Squaring Circuit Design for DSP Applications

IEEE Transactions on Emerging Topics in Computing

Mohammad Saeed Ansari

Bruce F. Cockburn

Jie Han

2020/4/24

High-throughput FPGA-based Hardware Accelerators for Deflate Compression and Decompression Using High-Level Synthesis

IEEE Access

Morgan Ledon

Bruce F Cockburn

Jie Han

2020/3/30

Improving the Accuracy and Hardware Efficiency of Neural Networks Using Approximate Multipliers

IEEE Transactions on Very Large Scale Integration (VLSI) Systems

Mohammad Saeed Ansari

Vojtech Mrazek

Bruce F Cockburn

Lukas Sekanina

Zdenek Vasicek

...

2019/10/8

See List of Professors in Bruce F. Cockburn University(University of Alberta)

Co-Authors

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