Abe S. (1989). Theories on the Hopfield neural networks Proc IEEE Int J Conf Neural Networks. 1

Abe S. (1993). Global convergence and suppression of spurious states of the Hopfield neural networks IEEE Trans Circuits And Systems. 40

Abe S. (1996). Convergence acceleration of the Hopfield neural network by optimizing integration step sizes. IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society. 26 [PubMed]

Abe S, Gee AH. (1995). Global convergence of the Hopfield neural network with nonzero diagonal elements IEEE Trans Circuits Systems. 42

Algaba A, Merino M, Freire E, Gamero E, Rodriguez-Luis A. (2003). Some results on Chuas equation near a triple-zero linear degeneracy Int J Bifur Chaos. 13

Bharitkar S, Tsuchiya K, Takefuji Y. (1999). Microcode optimization with neural networks. IEEE transactions on neural networks. 10 [PubMed]

Bronshtein I, Semendyayev K, Musiol G, Muehlig H. (2004). Handbook of mathematics.

Chen T, Amari SI. (2001). New theorems on global convergence of some dynamical systems. Neural networks : the official journal of the International Neural Network Society. 14 [PubMed]

Ciarlet P, Lions J. (2002). Handbook of numerical analysis.

Demmel J. (2000). Hermitian eigenproblems Templates for the solution of algebraic eigenvalue problems: A practical guide.

Feng J, Brown D. (1998). Fixed-point attractor analysis for a class of neurodynamics Neural Comput. 10

Golub GH, van_Loan CF. (1996). Matrix computations.

Guckenheimer J, Holmes P. (1983). Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields, 2nd edition..

Hirsch MW, Smale S. (1974). Differential Equations, Dynamical Systems and Linear Algebra.

Hopfield JJ. (1984). Neurons with graded response have collective computational properties like those of two-state neurons. Proceedings of the National Academy of Sciences of the United States of America. 81 [PubMed]

Hopfield JJ, Tank DW. (1985). "Neural" computation of decisions in optimization problems. Biological cybernetics. 52 [PubMed]

Horn RA, Johnson CR. (1985). Matrix analysis.

Joya G, Sandoval F, Atencia MA. (1997). Associating arbitrary-order energy functions to an artificial neural network: Implications concerning the resolution of optimization problems Neurocomputing. 14

Joya G, Sandoval F, Atencia MA. (2002). Hopfield neural networks for optimization: Study of the different dynamics Neurocomputing. 43

Joya G, Sandoval F, Atencia MA. (2003). Hopfield neural networks for parametric identification of a robotic system Proc. Engineering Application of Neural Networks Conference (EANN 2003), Malaga (Spain).

Joya G, Sandoval F, Atencia MA. (2003). Spurious minima and basins of attraction in higher-order Hopfield networks Computational methods in neural modeling.

Juang JC. (1999). Stability analysis of Hopfield-type neural networks. IEEE transactions on neural networks. 10 [PubMed]

Matsuda S. (1998). "Optimal" Hopfield network for combinatorial optimization with linear cost function. IEEE transactions on neural networks. 9 [PubMed]

Matsuda S. (2002). Optimal neural representation of higher order for traveling salesman problems Electronics and Communications in Japan (part 2). 85

Pardalos PM, Resende MG. (2002). Handbook of applied optimization.

Samad T, Harper P. (1990). High-order Hopfield and Tank optimization networks Parallel Computing. 16

Schropp J. (1995). Using dynamical systems methods to solve minimization problems Appl Numer Math. 18

Schropp J. (2000). One-step and multistep procedures for constrained minimization problems IMA J Numer Anal. 20

Sejnowski TJ. (1986). Higher-order Boltzmann machines Neural networks for computing.

Smith KA. (1999). Neural networks for combinatorial optimization: A review of more than a decade of research INFORMS J Comput. 11

Stuart A, Humphries A. (1996). Dynamical systems and numerical analysis.

Takefuji Y, Lee KC. (1991). Artificial neural networks for four-coloring map problems and K-colorability problems IEEE Trans Circuits Systems. 38

Tino P, Horne BG, Giles CL. (2001). Attractive periodic sets in discrete-time recurrent networks (with emphasis on fixed-point stability and bifurcations in two-neuron networks). Neural computation. 13 [PubMed]

Vidyasagar M. (1995). Minimum-seeking properties of analog neural networks with multilinear objective functions IEEE Trans Auto Control. 40

Wilson GV, Pawley GS. (1988). On the stability of the Travelling Salesman Problem algorithm of Hopfield and Tank. Biological cybernetics. 58 [PubMed]

Zufiria PJ, Riaza R. (2002). Discretization of implicit ODEs for singular root-finding problems J Comput Appl Math. 140