Neural computing

A Stochastic Approach to Combinatorial Optimization and Neural Computing. John Wiley Sons, New York, 1989. 

N. Bhat and T. J. McAvoy, "Dynamic Process Modeling via Neural Computing," paper presented atMJOE National Meeting, San Francisco, 1989. 

Garrido L, Gomez S, Roca J. Improved multidimensional scaling analysis using neural networks with distance-error backpropagation. Neural Comput 1999 11 595-600. 

The past decade has seen a dramatic increase in the number of reported applications of neural computing in pharmaceutical formulation [29-32]. Applications now cover a variety of formulations—for example, immediate and controlled release tablets, skin creams, hydrogel ointments, liposomes and emulsions, and film coatings. The following examples are by no means exhaustive, but they show where neural computing has been used successfully in modeling formulations. 

Although there is a great deal of interest in neural computing, quantified information on the benefits has been harder to find. From the applications described above in this chapter, benefits that could be seen included... 

In a survey [68] of the use of 93 neural computing applications in 75 UK companies covering all business sectors, the major benefits identified were improved quality, improved response times, and increased productivity. Eighty-four percent of users were satisfied or very satisfied with their systems, with only three percent expressing dissatisfaction. Business benefits specifically for the domain of product formulation (albeit for nonpharmaceuticals) have been given as [15]... 

Rowe RC, Colbourn EA. Applications of neural computing in formulation. Pharmaceutical Visions 2002. Spring Edition, 4-7. 

Hussain AS, Yu X, Johnson RD. Application of neural computing in pharmaceutical product development. Pharm Res 1991 8 1248-52. 

Rees C. Neural Computing—Learning Solutions—User Survey. Department of Trade and Industry, London, UK, 1996. 

Hartman, E., Keeler, K., and Kowalski, J. K., Layered Neural Networks with Gaussian hidden rmits as uttiversal approximators. Neural Comput. 2, 210 (1990). 

Moody, J and Darken, C. J., Fast learning in networks of locally-tuned processing units. Neural Comput. 1, 281 (1989). 

Platt, J., A resource-allocating network for function interpolation. Neural Comput. 3, 213 (1991)... 

R. Beale and T. Jackson, Neural Computing An Introduction. Institute of Physics Publishing, Bristol, 1992. 

P.D. Wasserman, Neural Computing Theory and Practice. Van Nostrand Reinhold, New York, 1989. 

R. Tibshirani, A comparison of some error estimates for neural network models. Neural Computation, 8(1995) 152-163. 

J. Park and I.W. Sandberg, Universal approximation using radial basis function networks. Neural Computation, 3 (1991) 246-257. 

Maren, A., Harston, C., and Rap, R., Handbook of Neural Computing Applications. Academic Press, New York. (1990). 

RC Rowe, RJ Roberts. Artifical intelligence in pharmaceutical product formulation neural computing and emerging technologies. PSTT l(5) 200-205, 1998. 

Cartwright, H.M., Investigation of structure-biodegradability relationships in polychlorinated biphenyls using self-organising maps, Neural Comput. Apps., 11, 30, 2002. 

Two of the most accessible books in the area are Neural Computing An Introduction, by Beale and Jackson10 and Neural Networks for Chemists, by Zupan and Gasteiger.11 Neither book is a recent publication, but both provide an introduction that is set at a suitable level if you have had little previous contact with ANNs. 

Hertz, J. Krogh, A. Palmer, R. G., Introduction to the Theory of Neural Computation, Addison-Wesley Redwood City, CA, 1991... 

A.J. Maren (editor) Handbook of neural computing applications, J. Wiley and sons, (London, UK) 1991... 

J. Hertz, A. Krogh, R.G. Palmer Introduction to the theory if Neural Computation Vol.l, Addison Wesley, New York (NY,USA) 1991... 

Neural Computing a technology handbook for Professional II/plus users, NeuralWare Inc., Pittsburgh (USA) 1993... 

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