Bachmann, C. M., Cooper, L. N., Dembo, A., and Zeitouni, O. (1987). "A Relaxation Model for Memory with High Storage Density," Proc. of the National Academy of Sciences, USA, 84, 7529-7531.

Bäck, T. (1993). "Optimal Mutation Rates in Genetic Search," Proceedings of the Fifth International Conference on Genetic Algorithms (Urbana-Champaign 1993), S. Forrest, Editor, 2-8. Morgan Kaufmann, San Mateo.

Baird, B. (1990). "Associative Memory in a Simple Model of Oscillating Cortex," in Advances in Neural Information Processing Systems 2 (Denver 1989) D. S. Touretzky, Editor, 68-75. Morgan Kaufmann, San Mateo.

Baird, B. and Eeckman, F. (1993). "A Normal Form Projection Algorithm for Associative Memory," in Associative Neural Memories: Theory and Implementation, M. H. Hassoun, Editor, 135-166. Oxford University Press, New York.

Baldi, P. (1991). "Computing with Arrays of Bell-Shaped and Sigmoid Functions," in Neural Information Processing Systems 3 (Denver 1990), R. P. Lippmann, J. E. Moody, and D. S. Touretzky, Editors, 735-742. Morgan Kaufmann, San Mateo.

Baldi, P. and Chauvin, Y. (1991). "Temporal Evolution of Generalization during Learning in Linear Networks," Neural Computation, 3(4), 589-603.

Baldi, P. and Hornik, K. (1989). "Neural Networks and Principal Component Analysis: Learning from Examples Without Local Minima," Neural Networks, 2(1), 53-58.

Barto, A. G. (1985). "Learning by Statistical Cooperation of Self-Interested Neuron-Like Computing Elements," Human Neurobiology, 4, 229-256.

Barto, A. G. and Anandan, P. (1985). "Pattern Recognizing Stochastic Learning Automata," IEEE Trans. on Systems, Man, and Cybernetics, SMC-15, 360-375.

Barto, A. G. and Jordan, M. I. (1987). "Gradient Following without Backpropagation in Layered Networks," in IEEE First International Conference on Neural Networks (San Diego 1987), M. Caudill and C. Butler, Editors, vol. II, 629-636. IEEE, New York.

Barto, A. G. and Singh, S. P. (1991). "On The Computational Economics of Reinforcement Learning," in Connectionist Models: Proceedings of the 1990 Summer School (Pittsburgh 1990), D. S. Touretzky, J. L. Elman, T. J. Sejnowski, and G. E. Hinton, Editors, 35-44, Morgan Kaufmann, San Mateo.

Barto A. G., Sutton, R. S., and Anderson, C. W. (1983). "Neuronlike Adaptive Elements That Can Solve Difficult Learning Control Problems," IEEE Trans. System. Man, and Cybernetics, SMC-13(5), 834-846.

Batchelor, B. G. (1969). Learning Machines for Pattern Recognition, Ph.D. thesis, University of Southampton, Southampton, England.

Batchelor, B. G. (1974). Practical Approach to Pattern Classification. Plenum, New York.

Batchelor, B. G. and Wilkins, B. R. (1968). "Adaptive Discriminant Functions," Pattern Recognition, IEEE Conf. Publ. 42, 168-178.

Battiti, R. (1992). "First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method," Neural Computation, 4(2), 141-166.

Baum, E. B. (1988). "On the Capabilities of Multilayer Perceptrons," Journal of Complexity, 4, 193-215.

Baum, E. (1989). "A Proposal for More Powerful Learning Algorithms," Neural Computation, 1(2), 201-207.

Baum, E. and Haussler, D. (1989). "What Size Net Gives Valid Generalization?" Neural Computation, 1(1), 151-160.

Baum, E. B. and Wilczek, F. (1988). "Supervised Learning of Probability Distributions by Neural Networks," in Neural Information Processing Systems (Denver 1987), D. Z. Anderson, Editor, 52-61, American Institute of Physics, New York.

Baxt, W. G. (1990). "Use of Artificial Neural Network for Data Analysis in Clinical Decision-Making: The Diagnosis of Acute Coronary Occlusion," Neural Computation, 2(4), 480-489.

Becker, S. and Le Cun, Y. (1989). "Improving the Convergence of Back-Propagation Learning with Second Order Methods," in Proceedings of the 1988 Connectionist Models Summer School (Pittsburgh 1988), D. Touretzky, G. Hinton, and T. Sejnowski, Editors, 29-37. Morgan Kaufmann, San Mateo.

Beckman, F. S. (1964). "The Solution of Linear Equations by the Conjugate Gradient Method," in Mathematical Methods for Digital Computers, A. Ralston and H. S. Wilf, Editors. Wiley, New York.

Belew, R., McInerney, J., and Schraudolph, N. N. (1990). "Evolving Networks: Using the Genetic Algorithm with Connectionist Learning," CSE Technical Report CS90-174, University of California, San Diego.

Benaim, M. (1994). "On Functional Approximation with Normalized Gaussian Units," Neural Computation, 6(2), 319-333.

Benaim, M. and Tomasini, L. (1992). "Approximating Functions and Predicting Time Series with Multi-Sigmoidal Basis Functions," in Artificial Neural Networks, J. Aleksander and J. Taylor, Editors, vol. 1, 407-411. Elsevier Science Publisher B. V., Amsterdam.

Bilbro, G. L., Mann, R., Miller, T. K., Snyder, W. E., van den Bout, D. E., and White, M. (1989). "Optimization by Mean Field Annealing," in Advances in Neural Information Processing Systems I (Denver 1988), Touretzky, D. S., 91-98. Morgan Kaufmann, San Mateo.

Bilbro, G. L. and Snyder, W. E. (1989). "Range Image Restoration Using Mean Field Annealing," in Advances in Neural Information Processing Systems I (Denver 1988), Touretzky, D. S., 594-601. Morgan Kaufmann, San Mateo.

Bilbro, G. L., Snyder, W. E., Garnier, S. J., and Gault, J. W. (1992). "Mean Field Annealing: A Formalism for Constructing GNC-like Algorithms," IEEE Transactions on Neural Networks, 3(1), 131-138.

Bishop, C. (1991). "Improving the Generalization Properties of Radial Basis Function Neural Networks," Neural Computation, 3(4), 579-588.

Bishop, C. (1992). "Exact Calculation of the Hessian Matrix for the Multilayer Perceptron," Neural Computation, 4(4), 494-501.

Block, H. D. and Levin, S. A. (1970). "On the Boundedness of an Iterative Procedure for Solving a System of Linear Inequalities," Proc. American Mathematical Society, 26, 229-235.

Blum, A. L. and Rivest, R. (1989). "Training a 3-Node Neural Network is NP-Complete," Proceedings of the 1988 Workshop on Computational Learning Theory, 9-18, Morgan Kaufmann, San Mateo.

Blum, A. L. and Rivest, R. (1992). "Training a 3-Node Neural Network is NP-Complete," Neural Networks, 5(1), 117-127.

Blumer, A., Ehrenfeucht, A., Haussler, D., and Warmuth, M. (1989). "Learnability and the Vapnik-Chervonenkis Dimension," JACM, 36(4), 929-965.

Boole, G. (1854). An Investigation of the Laws of Thought. Dover, NY.

Bounds, D. G., Lloyd, P. J., Mathew, B., and Wadell, G. (1988). "A Multilayer Perceptron Network for the Diagnosis of Low Back Pain," in Proc. IEEE International Conference on Neural Networks (San Diego 1988), vol. II, 481-489

Bourlard, H. and Kamp, Y. (1988). "Auto-Association by Multilayer Perceptrons and Singular Value Decomposition," Biological Cybernetics, 59, 291-294.

van den Bout, D. E. and Miller, T. K. (1988). "A Traveling Salesman Objective Function that Works," in IEEE International Conference on Neural Networks (San Diego 1988), vol. II, 299-303. IEEE, New York.

van den Bout, D. E. and Miller, T. K. (1989). "Improving the Performance of the Hopfield-Tank Neural Network Through Normalization and Annealing," Biological Cybernetics, 62, 129-139.

Bromley, J. and Denker, J. S. (1993). "Improving Rejection Performance on Handwritten Digits by Training with 'Rubbish'," Neural Computation, 5(3), 367-370.

Broomhead, D. S. and Lowe, D. (1988). "Multivariate Functional Interpolation and Adaptive Networks," Complex Systems, 2, 321-355.

Brown, R. R. (1959). "A Generalized Computer Procedure for the Design of Optimum Systems: Parts I and II," AIEE Transactions, Part I: Communications and Electronics, 78, 285-293.

Brown, R. J. (1964). Adaptive Multiple-Output Threshold Systems and Their Storage Capacities, Ph.D. Thesis, Tech. Report 6771-1, Stanford Electron. Labs, Stanford University, CA.

Brown, M., Harris, C. J., and Parks, P. (1993). "The Interpolation Capabilities of the Binary CMAC," Neural Networks, 6(3), 429-440.

Bryson, A. E. and Denham, W. F. (1962). "A Steepest-Ascent Method for Solving Optimum Programming Problems," J. Applied Mechanics, 29(2), 247-257.

Bryson, A. E. and Ho, Y.-C. (1969). Applied Optimal Control. Blaisdell, New York.

Burke, L. I. (1991). "Clustering Characterization of Adaptive Resonance," Neural Networks, 4(4), 485-491.

Burshtien, D. (1993). "Nondirect Convergence Analysis of the Hopfield Associative Memory," in Proc. World Congress on Neural Networks (Portland 1993), vol. II, 224-227. LEA, Hillsdale, NJ.

Butz, A. R. (1967). "Perceptron Type Learning Algorithms in Nonseparable Situations," J. Math Anal. and Appl., 17, 560-576. Also, see Ph.D. Dissertation, University of Minnesota, 1965.