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—A novel fourth-order half-mode substrate integrated waveguide (HMSIW) filter with dual-mode microstrip resonator is presented. The dual-mode resonator is etched on the top metal layer of HMSIW cavity, so the size can be reduced greatly. The filter has compact size and wide stopband in comparison with conventional SIW filters. Microstrip resonators and cavity resonators are integrated in one filter to achieve the goal of smaller size and better performance. Two filter samples are designed and fabricated, with good agreement between the measured and the simulated S-parameters.
The optimization of the desired autonomous underwater vehicle (AUV) trajectory modeling and AUV trajectory tracking control in the benthonic hydrothermal area were studied. In the conventional trajectory tracking model construction methods, the time points were roughly combined with the position points of the planned path, making it difficult to produce a smooth trajectory. Although the spline interpolation method was an ideal option for smooth curves, a great number of points were needed for a complex desired trajectory mode. In response to the demanding requirements of AUV trajectory tracking control in the benthonic hydrothermal area, an under-actuated test platform was first established, and the cubic spline interpolation was adopted to process the preset path points for a smooth desired trajectory. An improved slime mold algorithm (SMA) was put forward to optimize the interpolating points used in the trajectory modeling. The Levy flight technology and the compactness technique to speed up the search process and increase the search accuracy. The simulation experiments were conducted in comparison with the artificial fish swarm algorithm (AFSA), the particle swarm optimization (PSO), and the compact cuckoo search (CCS). The results showed that the improved SMA shortened the search process, effectively avoided the local extreme values, and generated a high-precision desired trajectory model in a shorter time. The pool test also verified the feasibility and effectiveness of the proposed method. The method proposed in this study can satisfy the modeling of benthonic hydrothermal trajectory with a fewer number of nodes, faster search progress and search accuracy.
Abstract Objective To update the literature and provide a systematic review of image‐based artificial intelligence (AI) applications in otolaryngology, highlight its advances, and propose future challenges. Data Sources Web of Science, Embase, PubMed, and Cochrane Library. Review Methods Studies written in English, published between January 2020 and December 2022. Two independent authors screened the search results, extracted data, and assessed studies. Results Overall, 686 studies were identified. After screening titles and abstracts, 325 full‐text studies were assessed for eligibility, and 78 studies were included in this systematic review. The studies originated from 16 countries. Among these countries, the top 3 were China (n = 29), Korea (n = 8), the United States, and Japan (n = 7 each). The most common area was otology (n = 35), followed by rhinology (n = 20), pharyngology (n = 18), and head and neck surgery (n = 5). Most applications of AI in otology, rhinology, pharyngology, and head and neck surgery mainly included chronic otitis media (n = 9), nasal polyps (n = 4), laryngeal cancer (n = 12), and head and neck squamous cell carcinoma (n = 3), respectively. The overall performance of AI in accuracy, the area under the curve, sensitivity, and specificity were 88.39 ± 9.78%, 91.91 ± 6.70%, 86.93 ± 11.59%, and 88.62 ± 14.03%, respectively. Conclusion This state‐of‐the‐art review aimed to highlight the increasing applications of image‐based AI in otorhinolaryngology head and neck surgery. The following steps will entail multicentre collaboration to ensure data reliability, ongoing optimization of AI algorithms, and integration into real‐world clinical practice. Future studies should consider 3‐dimensional (3D)‐based AI, such as 3D surgical AI.
In power electronics system, high frequency range CM noise suppression is a great challenge on the issue of conducted EMI. People may think that a perfect EMI filter with little self parasitics and mutual parasitics would suppress HF noise well. However, it will be shown that the practice story is different. In this paper, besides the parasitics in EMI filter, some other factors which increase the difficultly of high frequency range CM noise suppression are discussed. HF noise model and noise transmitting path are given. Based on the noise model, noise suppression techniques are analyzed and verified with experimental results.
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