| 1. |
- Feng, Xingxing, et al.
(författare)
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Human recognition with the optoelectronic reservoir-computing-based micro-Doppler radar signal processing
- 2022
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Ingår i: Applied Optics. - : Optica Publishing Group (formerly OSA). - 1559-128X .- 2155-3165. ; 61:19, s. 5782-5789
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Tidskriftsartikel (refereegranskat)abstract
- Current perception and monitoring systems, such as human recognition, are affected by several environmental factors, such as limited light intensity, weather changes, occlusion of targets, and public privacy. Human recognition using radar signals is a promising direction to overcome these defects; however, the low signal-to-noise ratio of radar signals still makes this task challenging. Therefore, it is necessary to use suitable tools that can efficiently deal with radar signals to identify targets. Reservoir computing (RC) is an efficient machine learning scheme that is easy to train and demonstrates excellent performance in processing complex time-series signals. The RC hardware implementation structure based on nonlinear nodes and delay feedback loops endows it with the potential for real-time fast signal processing. In this paper, we numerically study the performance of the optoelectronic RC composed of optical and electrical components in the task of human recognition with noisy micro-Doppler radar signals. A single-loop optoelectronic RC is employed to verify the application of RC in this field, and a parallel dual-loop optoelectronic RC scheme with a dual-polarization Mach–Zehnder modulator (DPol-MZM) is also used for performance comparison. The result is verified to be comparable with other machine learning tools, which demonstrates the ability of the optoelectronic RC in capturing gait information and dealing with noisy radar signals; it also indicates that optoelectronic RC is a powerful tool in the field of human target recognition based on micro-Doppler radar signals.
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| 2. |
- Feng, Xingxing, et al.
(författare)
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Numerical Study of Parallel Optoelectronic Reservoir Computing to Enhance Nonlinear Channel Equalization
- 2021
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Ingår i: Photonics. - : MDPI AG. - 2304-6732. ; 8:10
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Tidskriftsartikel (refereegranskat)abstract
- Nonlinear impairment is one of the critical limits to enhancing the performance of high-speed communication systems. Traditional digital signal processing (DSP)-based nonlinear channel equalization schemes are influenced by limited bandwidth, high power consumption, and high processing latency. Optoelectronic reservoir computing (RC) is considered a promising optical signal processing (OSP) technique with merits such as large bandwidth, high power efficiency, and low training complexity. In this paper, optoelectronic RC was employed to solve the nonlinear channel equalization problem. A parallel optoelectronic RC scheme with a dual-polarization Mach-Zehnder modulator (DPol-MZM) is proposed and demonstrated numerically. The nonlinear channel equalization performance was greatly enhanced compared with the traditional optoelectronic RC and the Volterra-based nonlinear DSP schemes. In addition, the system efficiency was improved with a single DPol-MZM.
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| 3. |
- Feng, Xingxing, et al.
(författare)
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The Parallel Optoelectronic Reservoir Computing Based Nonlinear Channel Equalization
- 2021
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Ingår i: 2021 Optoelectronics Global Conference, OGC 2021. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 230-234
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Konferensbidrag (refereegranskat)abstract
- The optoelectronic reservoir computing (RC) is considered as a promising optical signal processing technique for nonlinear channel equalization. In this paper, a parallel optoelectronic RC scheme with a dual-polarization Mach- Zehnder modulator (DPol-MZM) is proposed and demonstrated numerically. The nonlinear channel equalization performance is greatly enhanced compared with the traditional optoelectronic RC scheme and Volterra-based DSP scheme, since the nonlinear dynamics of RC are enriched from the dual-polarization methodology. Besides, the system efficiency is improved with a single DPol-MZM.
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| 4. |
- Ye, Kangpeng, et al.
(författare)
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Human Identification by Mean of Optoelectronic Reservoir Computing
- 2022
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Ingår i: 13TH INTERNATIONAL PHOTONICS AND OPTOELECTRONICS MEETINGS (POEM 2021). - : SPIE-Intl Soc Optical Eng.
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Konferensbidrag (refereegranskat)abstract
- As an improvement of the traditional recurrent neural networks (RNN), the reservoir computing (RC) only needs to train one output connection weight matrix linearly, which greatly reduces the number of machine learning network calculations. The optoelectronic RC can be realized with a delay feedback loop composed of optical and electrical devices. It has the advantages of lower power consumption and faster speed than the all-electric RC scheme. At the same time, it is easier to be controlled than the all-optical RC scheme. In this paper, we propose to employ the optoelectronic RC to process radar signals to distinguish different persons in the indoor environment. The radar signal required for the simulation is referred from the IDRad data set, which contains the echo signals of the frequency modulated continuous wave (FMCW) radar, and five persons of different ages are free to move around in the room, which is close to the real scene. First, the echo signal is processed and the micro-Doppler features are extracted, and each frame corresponds to a row vector. Then, this vector is used as the input signal of the optoelectronic RC. We numerically studied the impact of parameters such as the size of the RC and the regularization coefficient in the system. Finally, the classification accuracy of five targets reaches 87%.
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| 5. |
- Zhang, Xingxing, et al.
(författare)
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A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions
- 2018
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Ingår i: Applied Energy. - : Elsevier BV. - 0306-2619 .- 1872-9118. ; 230, s. 1034-1056
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Tidskriftsartikel (refereegranskat)abstract
- The emergence of renewable-energy-source (RES) envelope solutions, building retrofit requirements and advanced energy technologies brought about challenges to the existing paradigm of urban energy systems. It is envisioned that the building cluster approach—that can maximize the synergies of RES harvesting, building performance, and distributed energy management—will deliver the breakthrough to these challenges. Thus, this paper aims to critically review urban energy systems at the cluster level that incorporate building integrated RES solutions. We begin with defining cluster approach and the associated boundaries. Several factors influencing energy planning at cluster scale are identified, while the most important ones are discussed in detail. The closely reviewed factors include RES envelope solutions, solar energy potential, density of buildings, energy demand, integrated cluster-scale energy systems and energy hub. The examined categories of RES envelope solutions are (i) the solar power, (ii) the solar thermal and (iii) the energy-efficient ones, out of which solar energy is the most prevalent RES. As a result, methods assessing the solar energy potentials of building envelopes are reviewed in detail. Building density and the associated energy use are also identified as key factors since they affect the type and the energy harvesting potentials of RES envelopes. Modelling techniques for building energy demand at cluster level and their coupling with complex integrated energy systems or an energy hub are reviewed in a comprehensive way. In addition, the paper discusses control and operational methods as well as related optimization algorithms for the energy hub concept. Based on the findings of the review, we put forward a matrix of recommendations for cluster-level energy system simulations aiming to maximize the direct and indirect benefits of RES envelope solutions. By reviewing key factors and modelling approaches for characterizing RES-envelope-solutions-based urban energy systems at cluster level, this paper hopes to foster the transition towards more sustainable urban energy systems.
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