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- Liu, Yongjun, et al.
(författare)
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Depth from defocus (DFD) based on VFISTA optimization algorithm in micro/nanometer vision
- 2019
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Ingår i: Cluster Computing. - : SPRINGER. - 1386-7857 .- 1573-7543. ; 22, s. 1459-1467
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Tidskriftsartikel (refereegranskat)abstract
- In the three-dimensional (3D) morphological reconstruction of micro/nano-scale vision, the global depth from defocus algorithm (DFD) transforms the depth information of the scene into a dynamic optimization problem to solve. In order to improve the problem of dynamic optimization in the recovery process of global DFD, a variable-step-size fast iterative shrinkage-thresholding algorithm (VFISTA) is proposed. The traditional iterative shrinkage-thresholding algorithm (ISTA) is often used to solve this dynamic optimization problem in the global DFD method. The ISTA algorithm is an extension of the gradient descent method, which is close to the minimal value point of the optimization process, and the convergence speed is slow. What is more, the ISTA algorithm uses fixed step length in the iterative process, The search direction tend to be "orthogonal", prone to "saw tooth" phenomenon, so close to the minimum point when the convergence rate is slower. First, the VFISTA algorithm joins the acceleration operator on the basis of the ISTA algorithm. Further, it combines linear search method to find the optimal iteration length, and changes the limit of the ISTA algorithm step fixed. Finally, it is applied to the depth measurement of defocus scene in micro/nanometer scale vision. The experimental results show that the proposed fast depth from defocus algorithm based on VFISTA has faster convergent speed. Moreover, the precision of the measurement is obviously improved in micro/nanometer scale vision.
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- Wang, Desheng, et al.
(författare)
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Optimized Volume Control Architecture for Cascaded Audio System
- 2022
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Ingår i: IEEE transactions on consumer electronics. - : Institute of Electrical and Electronics Engineers (IEEE). - 0098-3063 .- 1558-4127. ; 68:2, s. 170-180
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Tidskriftsartikel (refereegranskat)abstract
- Cascaded audio systems (CASs) widely exist in consumer electronics, within which volume control is one of the most basic functions. However, the current volume adjustment schemes cannot automatically achieve optimal control, leading to performance degradation of CASs. Meanwhile, there is a lack of mathematical models and quantitative analysis between CASs performance and volume control position. In this study, an optimal volume control architecture named local processing and amplification (LPA) is proposed to minimize the volume control's adverse impact on CASs' performance automatically. First, a general CAS model is established through effective analysis and reasonable equivalence of diverse complicated CASs. Second, the quantitative relationship between the volume control and the CAS performance is theoretically analyzed using the noise figure theory, hence, the LPA architecture is proposed. Finally, the proposed LPA's performance improvement effect is analyzed and compared with the other volume controls in a wide volume range. Simulations and experiments using multiple indexes show that the signal-to-noise ratio (SNR) and the total harmonic distortion plus noise (THD+N) improvement of the proposed architecture are up to 5.2 dB and 4.8 dB, respectively, under a typical -9 dB volume.
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