Huang Junqian, Dynamics of Measurement System (in Chinese), Beijing: Publisher House of Defense Industry, 1996.
Tian Sheping, Application of recurrent network model on dynamic compensation of sensors, Journal of Measuring (in Chinese), 2003, 24(1): 49–51.
Tsung, T. T., Chang, H., Chen, L. C. et al., Analysis of dynamic characteristics of pressure sensors using square pressure wave theory and system identification, Measurement Science and Technology, 2003, 14: 1927–1937.
Zhang, Y., Liu, J. H., Zhang, Y. H. et al., Cross sensitivity reduction of gas sensors using genetic algorithm neural network, Optical Engineering, 2002, 41(3): 615–625.
Legin, A. V., Vlasov, Y. G., Rudniskaya, A. M. et al., Cross-sensitivity of chalcogenide glass sensors in solutions of heavy metal ions, Sensor and Actuators B, 1996, 334: 456–461.
Grys, S., Minkina, W., Fast temperature determination using two thermometers with different dynamical properties, Sensors and Actuators A, 2002, 100: 192–198.
Common, P., Independent component analysis, a new concept?, Signal Process, 1994, 36: 287–314.
Chi, C.Y., Chen, C.H., Cumulant-based inverse filter criteria for mimo blind deconvolution: properties, algorithms, and application to DS/CDMA systems in multipath, IEEE Transactions on Signal Processing, 2001, 49(7): 1282–1299.
Amari, S., Douglas, S.C., Cichoki, A. et al., Novel online adaptive learning algorithms for blind deconvolution using the natural gradient approach, Presented at 11th IFAC Symp. Syst. Ident. Kitakyushu, Japan, July 1997.
Douglas, S.C., Cichocki, A., Amari, S., Multichannel blind separation and deconvolution of sources with arbittrary distributions, Neural Networks Processing [1997], VII, Processing of the 1997 IEEE Workshop, 24–26, Sept. 1997, 436–445.
Cichocki, A., Zhang, L.Q., A daptive multichannel blind deconvolution using state-space model, Higher-Order Statistics, 1999, Proceedings of the IEEE Signal Processing Workshop, June 1999, 14–16.
Amari, S., Chen, T. P., Cichocki, A., Stability analysis of learning algorithm for blind source separation, Neural Networks Letter, 1997, 10(8): 1345–1351.
Park, H., Amari, S. I., Fukumizu, K., Adaptive natural gradient learning algorithms for various stochastic models, Neural Networks, 2000, 13: 755–764.
Cruces-Alvarez, S.A., Cichocki, A., Amari, S., On a new blind signal extraction algorithm: Different criteria and stability analysis, IEEE Signal Processing Letters, 2002, 9(8): 233–236.
Tsoi, A.C., Ma, L.S., Blind deconvolution of dynamical systems using a balanced parameterized state space approach, ICASSP, 2003 IV309–IV312.
Baccarelli, E., Galli, S., A new approach based on “soft statistics” to the nonlinear blind-deconvolution of unknown data channels, IEEE Transactions on Signal Processing, 2001, 49(7): 1481–1491.
Hyvärinen, A., Pajunen, P., Nonlinear independent component analysis: Existence and uniqueness results, Neural Networks, 1999, 12: 429–439.
Carmel, L., Levy, S., Lancet, D. et al., A feature extraction method for chemical sensors in electronic noses, Sensors and Actuators B, 2003, 93: 67–76.