Voir la notice de l'article provenant de la source Math-Net.Ru
[1] Pshibikhov A. V., Timofeev A. V., “Algoritm obucheniya i minimizatsii slozhnosti polinomialnykh raspoznayuschikh sistem”, Izv. AN SSSR. Tekhn. kibernetika, 1974, no. 5, 214–217
[2] Shibzukhov Z. M., “Neiroprotsessornye elementy polinomialnogo tipa iskusstvennykh neironnykh setei”, Dokl. Adygskoi AN, 4:1 (1999), 64–68
[3] Mel B. W., Conectionist robot motion planing, Acad. Press, New York, 1990
[4] Ballard D. H., Feldman J. A., “Connectionist models and their properties”, Cognitive Sci., 1982, no. 6, 205–254
[5] Gurney K. N., “Training nets of hardware relaizable sigma-pi units”, Neural Networks, 1992, no. 5, 289–303 | DOI
[6] Avsarkisyan G. S., “Rekurrentnye polinomialnye formy chastichnykh bulevykh funktsii”, Izv. AN SSSR. Tekhn. kibernetika, 1987, no. 4, 131–135 | MR
[7] Timofeev A. V., “Metody sinteza diofantovykh neirosetei minimalnoi slozhnosti”, Dokl. RAN, 345:1 (1995), 32–35 | MR | Zbl
[8] Shibzukhov Z. M., “Rekurrentnaya skhema postroeniya kortezhei mnogoznachnykh funktsii i obucheniya neironnykh setei”, Dokl. Adygskoi AN, 3:2 (1998), 45–51
[9] Shibzoukhov Z. M., “Constructive training of Boolean-valued neural networks of recognition and classification of the polynomial type”, Pattern Recognition and Image Analys., 11:1 (2001), 95–96
[10] Shibzukhov Z. M., “Rekurrentnye metody dlya konstruktivnogo obucheniya neitronnykh setei iz logiko-arifmeticheskikh sigma-arifmeticheskikh sigma-pi neironov”, Neirokompyutery: razrabotka i primenenie, 2002, no. 5–6, 50–57
[11] Gurevich I. B., Zhuravlev Yu. I., “Raspoznavanie obrazov i obrabotka izobrazhenii”, Iskusstvennyi intellekt, v. 2, kn. 2, Radio i svyaz, M., 1990
[12] Zhuravlev Yu. I., Problemy kibernetiki, 33, Nauka, M., 1978, 5–68