General rational approximation of Gaussian wavelet series and continuous‐time gm‐C filter implementation

Li, Mu; Sun, Yichuang

doi:10.1002/cta.2834

Cited by 7 publications

(2 citation statements)

References 37 publications

(43 reference statements)

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“…Augmented reality is a new technology developed based on virtual reality technology. Virtual reality technology requires a computer to generate a fully virtual space, which is extremely demanding for computers [6]. Augmented reality technology is based on the superimposition of virtual information or models on real scenes, which not only reduces the complex modelling process, but also enhances human involvement and sense of presence [7].…”

Section: Related Workmentioning

confidence: 99%

Privacy-Oriented Successive Approximation Image Position Follower Processing

Miao

Shao²,

Yan³

2021

Complexity

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In this paper, we analyze the location-following processing of the image by successive approximation with the need for directed privacy. To solve the detection problem of moving the human body in the dynamic background, the motion target detection module integrates the two ideas of feature information detection and human body model segmentation detection and combines the deep learning framework to complete the detection of the human body by detecting the feature points of key parts of the human body. The detection of human key points depends on the human pose estimation algorithm, so the research in this paper is based on the bottom-up model in the multiperson pose estimation method; firstly, all the human key points in the image are detected by feature extraction through the convolutional neural network, and then the accurate labelling of human key points is achieved by using the heat map and offset fusion optimization method in the feature point confidence map prediction, and finally, the human body detection results are obtained. In the study of the correlation algorithm, this paper combines the HOG feature extraction of the KCF algorithm and the scale filter of the DSST algorithm to form a fusion correlation filter based on the principle study of the MOSSE correlation filter. The algorithm solves the problems of lack of scale estimation of KCF algorithm and low real-time rate of DSST algorithm and improves the tracking accuracy while ensuring the real-time performance of the algorithm.

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Section: Related Workmentioning

confidence: 99%

Privacy-Oriented Successive Approximation Image Position Follower Processing

Miao

Shao²,

Yan³

2021

Complexity

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“…However, most of these studies focus on one type of wavelet basis and rarely involve a specific wavelet series. 33 In addition, the high-dimensional complexity of the fractional-order WT makes it difficult to construct the time-domain approximation function of the wavelet base. Therefore, we will directly construct the general approximation model of Gaussian-like wavelet bases from the fractional frequency domain, which is very important for selecting the optimal wavelet base and realizing the fractional-order analog wavelet filters.…”

Section: Gaussian-like Wavelet Transform In Analog Circuitmentioning

confidence: 99%

Design of a class of fractional-order analog wavelet filters

Li,

Zou,

Feng

et al. 2023

Journal of Algorithms & Computational Technology

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In this article, a methodology is proposed to implement fractional-order analog wavelet filters in the frequency domain. Under the proposed scheme, the fractional-order transfer function of the linear time-invariant system is used to approximate the Gaussian-like wavelet functions. Firstly, we construct a causal, stable, and physically achievable fractional-order mathematical approximation model. Then, the fractional-order mathematical approximation model is transformed into an optimization problem, and a hybrid particle swarm optimization algorithm is exploited to find its global optimal solution. At the same time, constraint terms are introduced to ensure the desired stability. The simulation results show that the fractional-order analog wavelet filters have higher approximation accuracy than the traditional integer-order analog wavelet filters. Furthermore, fractional-order analog wavelet filters can provide more precise control of the stopband attenuation rate, which is a key issue for many engineering applications.

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Design of programmable Gaussian‐derived wavelet filter for wearable biomedical sensor

Zhang

Zhao

Sun

2021

Circuit Theory & Apps

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To provide multiple options for specific application in biosignal processing, the programmable Gaussian‐derived Gm‐C wavelet filter has been proposed. To realize the programmable characteristic, the analog wavelet base with one numerator term is constructed by using hybrid artificial fish swarm algorithm. Also, the inverse follow‐the‐leader feedback Gm‐C filter structure with a switch array is employed. By programming switches only, Gaussian and Marr wavelet transforms can be realized flexibly with all component parameters unchanged. The seventh‐order programmable wavelet filter is designed as an example. Simulation results show that power consumption is only 141.68 pW at scale a = 0.1, with dynamic range of 42.6 dB and figure‐of‐merit of 2.05 × 10−13. Due to the programmability, the proposed design method can implement two wavelet filters with very low circuit complexity.

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General rational approximation of Gaussian wavelet series and continuous‐time g_m‐C filter implementation

Cited by 7 publications

References 37 publications

Privacy-Oriented Successive Approximation Image Position Follower Processing

Privacy-Oriented Successive Approximation Image Position Follower Processing

Design of a class of fractional-order analog wavelet filters

Design of programmable Gaussian‐derived wavelet filter for wearable biomedical sensor

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