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This paper presents a design for timing mismatch calibration in a TIADC (Time-Interleaved Analog-to-Digital Converter) with wideband inputs. By exploiting the approximately linear relationship between the autocorrelation properties of sub-ADCs and timing mismatch, we achieve rapid convergence of error estimation. A low-cost detection method is proposed based on the convergent monotonicity of the Least Mean Square (LMS) algorithm, which can automatically correct the calibration direction when the input signal goes beyond the Nyquist zone. Physical test results indicate that the spurs caused by timing mismatch can be suppressed by 26–30 dB using the proposed method. [ABSTRACT FROM AUTHOR]

State-of-charge balance is vital for allowing multiple energy storage units (ESUs) to make the most of stored energy and ensure safe operation. Concerning scenarios wherein boost converters are used as the interfaces between ESUs and loads, this paper proposes a balancing strategy for realizing consistent state-of-charge (SoC) levels and equal currents among different ESUs. This strategy is valid for both parallel and series applications. Its advantages also include its high precision of SoC equalization without extra sensors and fast convergence. A common outer voltage loop is used to accomplish tight voltage regulation, while multiple inner current loops are utilized to achieve current control and SoC balance simultaneously. Firstly, by introducing SoC-based current distribution ratios (CDRs) to modify current references online, the currents are gradually adjusted to eliminate SoC deviations. Secondly, to expedite the balancing process, current saturations are further adopted. Thirdly, the influences of accelerating factor and current limits in CDR expressions are analyzed, and their selection guidelines are subsequently provided. Fourthly, the controller design, consisting of a dual loop, is illustrated to guarantee sufficient stability margins. Fifthly, an experimental platform consisting of three battery ESUs is developed to verify the proposed strategy. [ABSTRACT FROM AUTHOR]

This brief proposes a signal-independent background calibration in pipeline-SAR analog-to-digital converters (ADCs) with a convergence-accelerated technique. To achieve signal independence, an auxiliary capacitor array CA is introduced to pre-inject a pseudo-random noise (PN) in the sampling phase to cancel out the opposite PN injection of the calibrated capacitor in the conversion phase, and CA is also used to realize the D/A function of the calibrated capacitor in the conversion phase. In this way, no matter what the signal is, the residue headroom remains unchanged even with PN injection. Moreover, the first sub-ADC is designed with extended conversion bits to quantize its own residue after delivering the conversion bits required by the first stage. Afterwards, this result is provided to the calibration algorithm to reduce the signal component and accelerate the convergence. Based on the simulation, the signal-to-noise and distortion ratio (SNDR) and spur-free dynamic range (SFDR) improve from 45.3 dB and 56.4 dB to 68.2 dB and 88.4 dB, respectively, after calibration. In addition, with the acceleration technique, convergence cycles decrease from 1.7 × 108 to 5.8 × 106. Moreover, no matter whether the input signal is DC, sine wave or band-limited white noise, the calibration all works normally. [ABSTRACT FROM AUTHOR]

Rotated object detection is an extension of object detection that uses an oriented bounding box instead of a general horizontal bounding box to define the object position. It is widely used in remote sensing images, scene text, and license plate recognition. The existing rotated object detection methods usually add an angle prediction channel in the bounding box prediction branch, and smooth L 1 loss is used as the regression loss function. However, we argue that smooth L 1 loss causes a sudden change in loss and slow convergence due to the angle solving mechanism of open CV (the angle between the horizontal line and the first side of the bounding box in the counter-clockwise direction is defined as the rotation angle), and this problem exists in most existing regression loss functions. To solve the above problems, we propose a decoupling modulation mechanism to overcome the problem of sudden changes in loss. On this basis, we also proposed a constraint mechanism, the purpose of which is to accelerate the convergence of the network and ensure optimization toward the ideal direction. In addition, the proposed decoupling modulation mechanism and constraint mechanism can be integrated into the popular regression loss function individually or together, which further improves the performance of the model and makes the model converge faster. The experimental results show that our method achieves 75.2% performance on the aerial image dataset DOTA (OBB task), and saves more than 30% of computing resources. The method also achieves a state-of-the-art performance in HRSC2016, and saved more than 40% of computing resources, which confirms the applicability of the approach. [ABSTRACT FROM AUTHOR]

This paper proposes a novel distributed secondary control of MGs for fast convergence considering asynchronous sampling. With the employment of the algorithm, optimal power sharing and voltage restoration are implemented simultaneously. First, the hierarchical control objectives concerned with economic operation and voltage quality are introduced. Then, the execution process of the fast convergence algorithm is described for weighted average state estimation, with the illustration of corresponding features and the application in cooperative control. Further, the relevant stability issue is discussed based on large-signal dynamic modeling and a sufficient stability condition is derived based on the Lyapunov–Krasovskii theory. Our approach offers superior reliability, flexibility and robustness because of the loose implementation in terms of its performance concern, which is essential when the distributed consensus protocol is likely to yield toward deviation or even instability under arbitrary sampling and delays. The effectiveness of the proposed methodology is verified via simulations. [ABSTRACT FROM AUTHOR]