Dr. Liang Yu

State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China

Dr. Liang Yu

State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China

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Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 January 2008 in Transactions of the American Mathematical Society

Journal Article

On initial segment complexity and degrees of randomness

Joseph Miller

Liang Yu

One approach to understanding the fine structure of initial segment complexity was introduced by Downey, Hirschfeldt and LaForte. They define

X\leq _K Y

to mean that

(\forall n)\; K(X\upharpoonright n)\leq K(Y\upharpoonright n)+O(1)

. The equivalence classes under this relation are the

K

-degrees . We prove that if

X\oplus Y

1

-random, then

X

and

Y

have no upper bound in the

K

-degrees (hence, no join). We also prove that

n

-randomness is closed upward in the

K

-degrees. Our main tool is another structure intended to measure the degree of randomness of real numbers: the

\textit {vL}

-degrees. Unlike the

K

-degrees, many basic properties of the

\textit {vL}

-degrees are easy to prove. We show that

X\leq _K Y

implies

X\leq _{\textit {vL}} Y

, so some results can be transferred. The reverse implication is proved to fail. The same analysis is also done for

\leq _C

, the analogue of

\leq _K

for plain Kolmogorov complexity. Two other interesting results are included. First, we prove that for any

Z\in 2^\omega

, a

1

-random real computable from a

1

Z

-random real is automatically

1

Z

-random. Second, we give a plain Kolmogorov complexity characterization of

1

-randomness. This characterization is related to our proof that

X\leq _C Y

implies

X\leq _{\textit {vL}} Y

1 June 2016 in Journal of Sound and Vibration

Journal Article

Spectral matrix completion by Cyclic Projection and application to sound source reconstruction from non-synchronous measurements

Liang Yu

Jerome Antoni

Quentin Leclere

17 May 2023 in Mechanical Systems and Signal Processing

Journal Article

A federated transfer learning method with low-quality knowledge filtering and dynamic model aggregation for rolling bearing fault diagnosis

Ran Wang

Fucheng Yan

Liang Yu

Changqing Shen

Xiong Hu

Jin Chen

1 November 2017 in Journal of Sound and Vibration

Journal Article

Acoustical source reconstruction from non-synchronous sequential measurements by Fast Iterative Shrinkage Thresholding Algorithm

Liang Yu

Jerome Antoni

Quentin Leclere

Weikang Jiang

1 August 2015 in Journal of Sound and Vibration

Journal Article

Reconstruction of sound quadratic properties from non-synchronous measurements with insufficient or without references: Proof of concept

Jerome Antoni

Liang Yu

Quentin Leclère

1 September 2022 in ISA Transactions

Journal Article

Sparse and low-rank decomposition of the time–frequency representation for bearing fault diagnosis under variable speed conditions

Ran Wang

Haitao Fang

Longjing Yu

Liang Yu

Jin Chen

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Dr. Liang Yu

Dr. Liang Yu

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