[1] Tolles W M, Nibler J W. McDonald J R, et al. A review of the theory and application of coherent anti-Stokes Raman spectroscopy (CARS)[J]. Applied Spectroscopy, 31, 253-271(1977). http://www.opticsinfobase.org/abstract.cfm?uri=as-31-4-253

[2] Lou C, Chen C, Sun Y P et al. Review of soot measurement in hydrocarbon-air flames[J]. Scientia Sinica(Technologica), 40, 946-958(2010).

[3] Rensberger K J, Jeffries J B, Copeland R A et al. Laser-induced fluorescence determination of temperatures in low pressure flames[J]. Applied Optics, 28, 3556-3566(1989). http://www.ncbi.nlm.nih.gov/pubmed/20555739

[4] Liu J, Kang Y Q, Gu Y B et al. Sparse tensor constrained for low dose CT reconstruction[J]. Acta Optica Sinica, 39, 0811004(2019).

[5] Cheng Q, Zhang X Y, Wang Z C et al. Simultaneous measurement of three-dimensional temperature distributions and radiative properties based on radiation image processing technology in a gas-fired pilot tubular furnace[J]. Heat Transfer Engineering, 35, 770-779(2014). http://www.tandfonline.com/doi/ref/10.1080/08832323.2013.838096

[6] Cai W W, Kaminski C F. Tomographic absorption spectroscopy for the study of gas dynamics and reactive flows[J]. Progress in Energy and Combustion Science, 59, 1-31(2017). http://www.sciencedirect.com/science/article/pii/S0360128516300685

[7] Yang W Q, Peng L H. Image reconstruction algorithms for electrical capacitance tomography[J]. Measurement Science and Technology, 14, R1-R13(2003). http://www.emeraldinsight.com/servlet/linkout?suffix=b12&dbid=16&doi=10.1108%2F03321640910958991&key=10.1088%2F0957-0233%2F14%2F1%2F201

[8] Song X Z, Xu Y B, Dong F. A spatially adaptive total variation regularization method for electrical resistance tomography[J]. Measurement Science and Technology, 26, 125401(2015). http://adsabs.harvard.edu/abs/2015MeScT..26l5401S

[9] Zhang X Y, Cheng Q, Lou C et al. An improved colorimetric method for visualization of 2-D, inhomogeneous temperature distribution in a gas fired industrial furnace by radiation image processing[J]. Proceedings of the Combustion Institute, 33, 2755-2762(2011). http://www.sciencedirect.com/science/article/pii/S1540748910002105

[10] Liu D, Yan J H, Wang F et al. Experimental reconstructions of flame temperature distributions in laboratory-scale and large-scale pulverized-coal fired furnaces by inverse radiation analysis[J]. Fuel, 93, 397-403(2012). http://www.sciencedirect.com/science/article/pii/S0016236111005412

[11] Liu L H, Man G L. Reconstruction of time-averaged temperature of non-axisymmetric turbulent unconfined sooting flame by inverse radiation analysis[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 78, 139-149(2003). http://www.sciencedirect.com/science/article/pii/S0022407302001863

[12] Sidky E Y, Pan X C. Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization[J]. Physics in Medicine & Biology, 53, 4777-4807(2008). http://europepmc.org/articles/PMC2630711/

[13] Cai W W, Li X S, Ma L. Practical aspects of implementing three-dimensional tomography inversion for volumetric flame imaging[J]. Applied Optics, 52, 8106-8116(2013). http://www.ncbi.nlm.nih.gov/pubmed/24513765

[14] Zhang B, Zhao M M, Liu Z G et al. Flame four-dimensional deflection tomography with compressed-sensing-revision reconstruction[J]. Optics and Lasers in Engineering, 83, 23-31(2016). http://www.sciencedirect.com/science/article/pii/S0143816616000610

[15] Huang G B, Zhu Q Y, Siew C K. Extreme learning machine: a new learning scheme of feedforward neural networks. [C]//2004 IEEE International Joint Conference on Neural Networks, July 25-29, 2004, Budapest, Hungary. New York: IEEE, 985-990(2004).

[16] Liu X, Wang X X, Hu H L et al. An extreme learning machine combined with Landweber iteration algorithm for the inverse problem of electrical capacitance tomography[J]. Flow Measurement and Instrumentation, 45, 348-356(2015). http://www.sciencedirect.com/science/article/pii/S0955598615001144

[17] Yu T, Cai W W, Liu Y Z. Rapid tomographic reconstruction based on machine learning for time-resolved combustion diagnostics[J]. Review of Scientific Instruments, 89, 043101(2018). http://www.ncbi.nlm.nih.gov/pubmed/29716336

[18] Liu D, Yan J H, Cen K F. On the treatment of scattering for three-dimensional temperature distribution reconstruction accuracy in participating medium[J]. International Journal of Heat and Mass Transfer, 54, 1684-1687(2011). http://www.sciencedirect.com/science/article/pii/S0017931010006381

[19] Li T J, Li S N, Yuan Y et al. Light field imaging analysis of flame radiative properties based on Monte Carlo method[J]. International Journal of Heat and Mass Transfer, 119, 303-311(2018).

[20] Gordon R, Bender R, Herman G T. Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography[J]. Journal of Theoretical Biology, 29, 471-481(1970). http://www.ncbi.nlm.nih.gov/pubmed/5492997

[21] Mo L D, Xu B Q. An improved TV image reconstruction algorithm[J]. Electronic Science and Technology, 29, 47-50(2016).

[23] Paige C C, Saunders M A. LSQR: an algorithm for sparse linear equations and sparse least squares[J]. ACM Transactions on Mathematical Software, 8, 43-71(1982). http://www.ams.org/mathscinet-getitem?mr=661121

[24] Shi Y, Eberhart R C. Empirical study of particle swarm optimization. [C]//1999 Congress on Evolutionary Computation-CEC99, July 6-9, 1999, Washington, DC, USA. New York: IEEE, 1945-1950(1999).

[25] Liu F S, Guo H S, Smallwood G J et al. Numerical modelling of soot formation and oxidation in laminar coflow non-smoking and smoking ethylene diffusion flames[J]. Combustion Theory and Modelling, 7, 301-315(2003). http://www.tandfonline.com/doi/abs/10.1088/1364-7830/7/2/305

[26] van Heeswijk M, Miche Y, Oja E et al. . GPU-accelerated and parallelized ELM ensembles for large-scale regression[J]. Neurocomputing, 74, 2430-2437(2011). http://www.sciencedirect.com/science/article/pii/S0925231211002517