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A new proposal of applying surrogate-modeling in Input-output Buffer Information Specification (IBIS) is presented. It saves the IBIS data storage resource, extends the model utility to various process-voltage-temperature (PVT) simulations and eliminates the data interpolation deviations.

An improved global navigation satellite system (GNSS)/inertial navigation system (INS) tightly coupled scheme based on a time-differenced carrier phase (TDCP) was proposed for a low-cost vehicle navigation system. The proposed scheme aims to improve the navigation performance and computational efficiency of the system for low-cost GNSS receivers and low-accuracy INS. The traditional measurement model based on the TDCP has either high accuracy with a large computational load or high efficiency with low accuracy. Considering both the positioning accuracy and computational burden, an accurate and efficient measurement model was derived in this paper. In positioning based on the carrier phase, it is an indispensable task to handle the cycle slips, especially small ones. However, the cycle slip of a certain moment only contaminates the current TDCP measurement, but not the subsequent TDCP measurements. Based on this characteristic of the TDCP measurement, a novel cycle slip processing strategy was proposed for the TDCP-GNSS/INS integration scheme, in which cycle slip is directly handled as a gross error with a robust extended Kalman filter (EKF). The vehicular test has been conducted to evaluate the performance of the improved TDCP-GNSS/INS integration scheme. Experiment results show: (a) compared with the traditional position error parameter-based measurement model, the proposed measurement model can improve the accuracy of the horizontal and vertical position by 58.4% and 12.5%, respectively. Compared with the traditional velocity error parameter-based measurement model, the proposed measurement model does not improve the positioning accuracy, but improves the computational efficiency by 25.2%. (b) The strategy of treating cycle slip as a gross error is feasible in the TDCP-GNSS/INS tightly coupled navigation system. Although a small cycle slip can seriously affect the positioning performance of the system, the robust EKF can effectively avoid the long-term harm caused by small cycle slips.

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. Significance As an early stage of Alzheimer’s disease (AD), the diagnosis of amnestic mild cognitive impairment (aMCI) has important clinical value for timely intervention of AD. Functional near-infrared spectroscopy (fNIRS)-based resting-state brain connectivity analysis, which could provide an economic and quick screening strategy for aMCI, remains to be extensively investigated. Aim This study aimed to verify the feasibility of fNIRS-based resting-state brain connectivity for evaluating brain function in patients with aMCI, and to determine an early screening model for auxiliary diagnosis. Approach The resting-state fNIRS was utilized for exploring the changes in functional connectivity of 64 patients with aMCI. The region of interest (ROI)-based and channel-based connections with significant inter-group differences have been extracted through the two-sample -tests and the receiver operating characteristic (ROC). These connections with specificity and sensitivity were then taken as features for classification. Results Compared with healthy controls, connections of the MCI group were significantly reduced between the bilateral prefrontal, parietal, occipital, and right temporal lobes. Specifically, the long-range connections from prefrontal to occipital lobe, and from prefrontal to parietal lobe, exhibited stronger identifiability (area under the ROC curve , ** ). Subsequently, the optimal classification accuracy of ROI-based connections was 71.59%. Furthermore, the most responsive connections were located between the right dorsolateral prefrontal lobe and the left occipital lobe, concomitant with the highest classification accuracy of 73.86%. Conclusion Our findings indicate that fNIRS-based resting-state functional connectivity analysis could support MCI diagnosis. Notably, long-range connections involving the prefrontal and occipital lobes have the potential to be efficient biomarkers.

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