[1] V. G. Veselago. Electrodynamics of substances with simultaneously negative values of sigma and μ. Sov. Phys. Usp., 10, 509-514(1968).

[2] R. Zhao, L. Huang, Y. Wang. Recent advances in multi-dimensional metasurfaces holographic technologies. PhotoniX, 1, 20(2020).

[3] X. Ding, Z. Wang, G. Hu, J. Liu, K. Zhang, H. Li, B. Ratni, S. N. Burokur, Q. Wu, J. Tan, C.-W. Qiu. Metasurface holographic image projection based on mathematical properties of Fourier transform. PhotoniX, 1, 16(2020).

[4] Q. Ma, Q. R. Hong, X. X. Gao, H. B. Jing, C. Liu, G. D. Bai, Q. Cheng, T. J. Cui. Smart sensing metasurface with self-defined functions in dual polarizations. Nanophotonics, 9, 3271-3278(2020).

[5] X. Ni, N. K. Emani, A. V. Kildishev, A. Boltasseva, V. M. Shalaev. Broadband light bending with plasmonic nanoantennas. Science, 335, 427(2012).

[6] N. Yu, P. Genevet, M. A. Kats, F. Aieta, J.-P. Tetienne, F. Capasso, Z. Gaburro. Light propagation with phase discontinuities: generalized laws of reflection and refraction. Science, 334, 333-337(2011).

[7] D. Schurig, J. J. Mock, B. J. Justice, S. A. Cummer, J. B. Pendry, A. F. Starr, D. R. Smith. Metamaterial electromagnetic cloak at microwave frequencies. Science, 314, 977-980(2006).

[8] J. Li, J. B. Pendry. Hiding under the carpet: a new strategy for cloaking. Phys. Rev. Lett., 101, 203901(2008).

[9] R. Liu, C. Ji, J. J. Mock, J. Y. Chin, T. J. Cui, D. R. Smith. Broadband ground-plane cloak. Science, 323, 366-369(2009).

[10] Q. Ma, Z. L. Mei, S. K. Zhu, T. Y. Jin, T. J. Cui. Experiments on active cloaking and illusion for Laplace equation. Phys. Rev. Lett., 111, 173901(2013).

[11] W. X. Jiang, T. J. Cui, Q. Cheng, J. Y. Chin, X. M. Yang, R. Liu, D. R. Smith. Design of arbitrarily shaped concentrators based on conformally optical transformation of nonuniform rational B-spline surfaces. Appl. Phys. Lett., 92, 264101(2008).

[12] Y. Lai, J. Ng, H. Chen, D. Han, J. Xiao, Z.-Q. Zhang, C. T. Chan. Illusion optics: the optical transformation of an object into another object. Phys. Rev. Lett., 102, 253902(2009).

[13] L. Chen, Q. Ma, Q. F. Nie, Q. R. Hong, H. Y. Cui, Y. Ruan, T. J. Cui. Dual-polarization programmable metasurface modulator for near-field information encoding and transmission. Photon. Res., 9, 116-124(2021).

[14] N. Kundtz, D. R. Smith. Extreme-angle broadband metamaterial lens. Nat. Mater., 9, 129-132(2010).

[15] W. X. Jiang, C.-W. Qiu, T. C. Han, Q. Cheng, H. F. Ma, S. Zhang, T. J. Cui. Broadband all-dielectric magnifying lens for far-field high-resolution imaging. Adv. Mater., 25, 6963-6968(2013).

[16] X. M. Yang, X. Y. Zhou, Q. Cheng, H. F. Ma, T. J. Cui. Diffuse reflections by randomly gradient index metamaterials. Opt. Lett., 35, 808-810(2010).

[17] T. J. Cui, M. Q. Qi, X. Wan, J. Zhao, Q. Cheng. Coding metamaterials, digital metamaterials and programmable metamaterials. Light Sci. Appl., 3, e218(2014).

[18] J. Li, Y. Zhang, J. Li, X. Yan, L. Liang, Z. Zhang, J. Huang, J. Li, Y. Yang, J. Yao. Amplitude modulation of anomalously reflected terahertz beams using all-optical active Pancharatnam–Berry coding metasurfaces. Nanoscale, 11, 5746-5753(2019).

[19] R. Y. Wu, L. Zhang, L. Bao, L. W. Wu, Q. Ma, G. D. Bai, H. T. Wu, T. J. Cui. Digital metasurface with phase code and reflection-transmission amplitude code for flexible full-space electromagnetic manipulations. Adv. Opt. Mater., 7, 1801429(2019).

[20] Q. Ma, Q. R. Hong, G. D. Bai, H. B. Jing, R. Y. Wu, L. Bao, Q. Cheng, T. J. Cui. Editing arbitrarily linear polarizations using programmable metasurface. Phys. Rev. Appl., 13, 021003(2020).

[21] Q. Ma, C. B. Shi, G. D. Bai, T. Y. Chen, A. Noor, T. J. Cui. Beam-editing coding metasurfaces based on polarization bit and orbital-angular-momentum-mode bit. Adv. Opt. Mater., 5, 1700548(2017).

[22] Q. Ma, L. Chen, H. B. Jing, Q. R. Hong, H. Y. Cui, Y. Liu, L. Li, T. J. Cui. Controllable and programmable nonreciprocity based on detachable digital coding metasurface. Adv. Opt. Mater., 7, 1901285(2019).

[23] G. Ding, K. Chen, X. Luo, J. Zhao, T. Jiang, Y. Feng. Dual-helicity decoupled coding metasurface for independent spin-to-orbital angular momentum conversion. Phys. Rev. Appl., 11, 044043(2019).

[24] J. Han, L. Li, H. Yi, Y. Shi. 1-bit digital orbital angular momentum vortex beam generator based on a coding reflective metasurface. Opt. Mater. Express, 8, 3470-3478(2018).

[25] Q. Zheng, Y. Li, Y. Han, M. Feng, Y. Pang, J. Wang, H. Ma, S. Qu, J. Zhang. Efficient orbital angular momentum vortex beam generation by generalized coding metasurface. Appl. Phys. A, 125, 136(2019).

[26] T. J. Cui, L. Li, S. Liu, Q. Ma, Q. Cheng. Information metamaterial systems. iScience, 23, 101403(2020).

[27] L. Li, T. J. Cui. Information metamaterials - from effective media to real-time information processing systems. Nanophotonics, 8, 703-724(2019).

[28] T. J. Cui, S. Liu, L. Zhang. Information metamaterials and metasurfaces. J. Mater. Chem. C, 5, 3644-3668(2017).

[29] Q. Ma, T. J. Cui. Information metamaterials: bridging the physical world and digital world. PhotoniX, 1, 1(2020).

[30] L. Zhang, X. Q. Chen, S. Liu, Q. Zhang, J. Zhao, J. Y. Dai, G. D. Bai, X. Wan, Q. Cheng, G. Castaldi, V. Galdi, T. J. Cui. Space-time-coding digital metasurfaces. Nat. Commun., 9, 4334(2018).

[31] T. J. Cui, S. Liu, G. D. Bai, Q. Ma. Direct transmission of digital message via programmable coding metasurface. Research, 2019, 2584509(2019).

[32] H. Zhao, Y. Shuang, M. Wei, T. J. Cui, P. D. Hougne, L. Li. Metasurface-assisted massive backscatter wireless communication with commodity Wi-Fi signals. Nat. Commun., 11, 3926(2020).

[33] Y. Shuang, H. Zhao, W. Ji, T. J. Cui, L. Li. Programmable high-order OAM-carrying beams for direct-modulation wireless communications. IEEE J. Emerg. Sel. Top. Circuits Syst., 10, 29-37(2020).

[34] G. Hinton, L. Deng, D. Yu, G. E. Dahl, A. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. N. Sainath, B. Kingsbury. Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups. IEEE Signal Process. Mag., 29, 82-97(2012).

[35] G. Pironkov, S. U. N. Wood, S. Dupont. Hybrid-task learning for robust automatic speech recognition. Comput. Speech Lang., 64, 101103(2020).

[36] A. Graves, A. R. Mohamed, G. Hinton. Speech recognition with deep recurrent neural networks. IEEE International Conference on Acoustics, Speech and Signal Processing, 6645-6649(2013).

[37] K. Lu. Intelligent recognition system for high precision image significant features in large data background. Cyber Security Intelligence and Analytics, 1056-1062(2020).

[38] T. Tong, X. Mu, L. Zhang, Z. Yi, P. Hu. MBVCNN: joint convolutional neural networks method for image recognition. AIP Conf. Proc., 1839, 020091(2017).

[39] H. Sun, Q. Zhang, H. Wang, A. Li. Research of images recognition method based on RBF neural network. 7th International Conference on System of Systems Engineering, 24-26(2012).

[40] K. Cho, B. Van Merrienboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, Y. J. C. Bengio. Learning phrase representations using RNN encoder-decoder for statistical machine translation(2014).

[41] C. Escolano, M. R. Costa-Jussa, J. A. R. Fonollosa. From bilingual to multilingual neural-based machine translation by incremental training. 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 236-242(2019).

[42] S. Kwon, B. H. Go, J. H. Lee. A text-based visual context modulation neural model for multimodal machine translation. Pattern Recogn. Lett., 136, 212-218(2020).

[43] C. He, Y. Wan, Y. Gu, F. L. Lewis. Integral reinforcement learning-based multi-robot minimum time-energy path planning subject to collision avoidance and unknown environmental disturbances. IEEE Control Syst. Lett., 5, 983-988(2021).

[44] B. Sangiovanni, G. P. Incremona, M. Piastra, A. Ferrara. Self-configuring robot path planning with obstacle avoidance via deep reinforcement learning. IEEE Control Syst. Lett., 5, 397-402(2021).

[45] J. Yoo, D. Jang, H. J. Kim, K. H. Johansson. Hybrid reinforcement learning control for a micro quadrotor flight. IEEE Control Syst. Lett., 5, 505-510(2021).

[46] Q. Zhang, X. Wan, S. Liu, J. Y. Yin, L. Zhang, T. J. Cui. Shaping electromagnetic waves using software-automatically-designed metasurfaces. Sci. Rep., 7, 3588(2017).

[47] L. L. Li, H. X. Ruan, C. Liu, Y. Li, Y. Shuang, A. Alu, C. W. Qiu, T. J. Cui. Machine-learning reprogrammable metasurface imager. Nat. Commun., 10, 1082(2019).

[48] T. Qiu, X. Shi, J. Wang, Y. Li, S. Qu, Q. Cheng, T. Cui, S. Sui. Deep learning: a rapid and efficient route to automatic metasurface design. Adv. Sci., 6, 1900128(2019).

[49] Q. Ma, G. D. Bai, H. B. Jing, C. Yang, L. Li, T. J. Cui. Smart metasurface with self-adaptively reprogrammable functions. Light Sci. Appl., 8, 98(2019).

[50] H. Li, H. Zhao, M. Wei, H. Ruan, Y. Shuang, T. J. Cui, P. del Hougne, L. Li. Intelligent electromagnetic sensing with learnable data acquisition and processing. Patterns, 1, 100006(2020).

[51] L. Li, Y. Shuang, Q. Ma, H. Li, H. Zhao, M. Wei, C. Liu, C. Hao, C.-W. Qiu, T. J. Cui. Intelligent metasurface imager and recognizer. Light Sci. Appl., 8, 97(2019).

[52] L. Li, T. J. Cui, W. Ji, S. Liu, J. Ding, X. Wan, Y. B. Li, M. Jiang, C.-W. Qiu, S. Zhang. Electromagnetic reprogrammable coding-metasurface holograms. Nat. Commun., 8, 197(2017).

[53] J. Wu, Z. Wang, L. Zhang, Q. Cheng, S. Liu, S. Zhang, J. Song, C. T. Jun. Anisotropic metasurface holography in 3D space with high resolution and efficiency. IEEE Trans. Antennas Propag., 69, 302-316(2020).

[54] C. Liu, Q. Ma, L. Li, T. J. Cui. Work in progress: intelligent metasurface holograms. 1st ACM International Workshop on Nanoscale Computing, Communication, and Applications, 45-48(2020).

[55] Z. Y. Zhou, J. Xia, J. Wu, C. L. Chang, X. Ye, S. G. Li, B. T. Du, H. Zhang, G. D. Tong. Learning-based phase imaging using a low-bit-depth pattern. Photon. Res., 8, 1624-1633(2020).

[56] R. Lopez, J. Regier, M. I. Jordan, N. Yosef. Information constraints on auto-encoding variational Bayes. 32nd Conference on Neural Information Processing Systems (NeurIPS), 6114-6125(2018).

[57] I. Deshpande, Z. Zhang, A. Schwing. Generative modeling using the sliced Wasserstein distance. IEEE Conference on Computer Vision and Pattern Recognition, 3483-3491(2018).

[58] M. Arjovsky, L. Bottou. Towards principled methods for training generative adversarial networks. 5th International Conference on Learning Representations (ICLR), 1-17(2017).

[59] V. M. Panaretos, Y. Zemely. Statistical aspects of Wasserstein distances(2019).

[60] M. Arjovsky, S. Chintala, L. Bottou. Wasserstein generative adversarial networks. 34th International Conference on Machine Learning (ICML), 214-223(2017).

[61] I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, A. Courville. Improved training of wasserstein GANs. 31st Annual Conference on Neural Information Processing Systems (NIPS), 5768-5778(2017).

[62] M. Mirza. Conditional generative adversarial nets(2014).

[63] P. Isola, J.-Y. Zhu, T. Zhou, A. A. Efros. Image-to-image translation with conditional adversarial networks. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5967-5976(2017).

[64] T.-C. Wang, M.-Y. Liu, J.-Y. Zhu, A. Tao, J. Kautz, B. Catanzaro. High-resolution image synthesis and semantic manipulation with conditional GANs. 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 8798-8807(2018).

[65] K. He, X. Zhang, S. Ren, J. Sun. Identity mappings in deep residual networks. 21st ACM Conference on Computer and Communications Security (CCS), 630-645(2016).

[66] S. Ioffe, C. Szegedy. Batch normalization: accelerating deep network training by reducing internal covariate shift. 32nd International Conference on Machine Learning (ICML), 448-456(2015).

[67] D. Ulyanov, A. Vedaldi. Instance normalization: the missing ingredient for fast stylization(2017).

[68] Y. LeCun, C. Cortes, C. J. C. Burges. The MNIST database of handwritten digits(2012).

[69] X. Zou, G. Zheng, Q. Yuan, W. Zang, R. Chen, T. Li, L. Li, S. Wang, Z. Wang, S. Zhu. Imaging based on metalenses. PhotoniX, 1, 2(2020).

[70] A. Ahad, M. Tahir, K. A. Yau. 5G-based smart healthcare network: architecture, taxonomy, challenges and future research directions. IEEE Access, 7, 100747(2019).