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Dao-Hang Sha

4 papers hereh-index 262.7k citations70 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author2
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.NE1
  • cs.RO1
  • eess.SY1
  • math.GM1
same name
  • Dao-Hang Sha — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20102021
most citedThree-dimensional Torques and Power of Horse Forelimb Joints at Trot

3 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

math.GM2021

On the Bounds of Stopping and Cycle Numbers in the Collatz Process

Daohang Sha

We study the stopping time and cycle structure of the normalized Collatz iteration using a binary sequence formalism. By introducing a recursive rooted sequence tree by Winkler (20…

cs.RO2011★ 3 cited

Three-dimensional Torques and Power of Horse Forelimb Joints at Trot

H. M. Clayton, D. H. Sha, D. R. Mullineaux

Reasons for Performing Study: Equine gait analysis has focused on 2D analysis in the sagittal plane, while descriptions of 3D kinetics and ground reaction force could provide more…

eess.SY2011★ 1 cited

An Optimization-Based Model for Full-body Reaching Movements

Daohang Sha, James S Thomas

Background The development of a simulation model of full body reaching tasks that can predict endeffector trajectories and joint excursions consistent with experimental data is a n…

cs.NE2010★ 1 cited

An optimized recursive learning algorithm for three-layer feedforward neural networks for mimo nonlinear system identifications

Daohang Sha, Vladimir B. Bajic

Back-propagation with gradient method is the most popular learning algorithm for feed-forward neural networks. However, it is critical to determine a proper fixed learning rate for…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.