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Figure 5.6 Neutral donor binding energy EDo in the 60 A CdTe quantum well as before, as a function of the donor position rd

In addition, De Morgan's rules (Section 7.2) apply not just to binary conjunctions and disjunctions: [De Morgan] -^(3k:R:T) = ( V k : R : - < T ) , [De Morgan] ^{Vk:R:T} = (3k : R : -T) . (11.42) (11.43)

Using the substitution w = e q, then when 9 = 0, w I, and when 6 = oo, w = 0. Also, remembering:

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The warning about existence of summations over an infinite range does not apply to universal or existential quantifications. Any universal or existential quantification you care to write down has meaning and the rules above apply.

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[Orr and Leen 1993] GB Orr, TK Leen, Momentum and Optimal Stochastic Search, in MC Mozer, P Smolensky, DS Touretzky, JL Elman, AS Weigend (eds), Proceedings of the 1993 Connectionist Models Summer School, Erlbaum Associates, 1993 [Ostrowski and Reynolds 1999] DA Ostrwoski, RG Reynolds, Knowledge-Based Software Testing Agent using Evolutionary Learning with Cultural Algorithms, IEEE International Congress on Evolutionary Computation, Vol 3, 1999, pp 1657 1663 [Pawlak 1982] Z Pawlak, Rough Sets, International Journal of Computer and Information Sciences, Vol 11, 1982, pp 341 356 [Pedersen et al 1996] MW Pedersen, LK Hansen, J Larsen, Pruning with Generalization Based Weight Saliencies: 7 OBD, 7 OBS, in DS Touretzky, MC Mozer, ME Hasselmo (eds), Advances in Neural Information Processing Systems, Vol 8, 1996, pp 521 528 [Plaut et al.

equation (5.56) therefore becomes:

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We have now seen four different quantifiers: summation, product, universal quantification and existential quantification. We have also seen that the rules governing the manipulation of these quantifiers have much in common. In this section, we generalize the rules to an arbitrary quantifier. The technical name for the process is abstraction; we 'abstract' from particular operators to an arbitrary associative and symmetric operator, which we denote by . The rules are grouped, as before, into rules for manipulating the dummy, rules for the range part and the term part, and trading rules. The process of abstraction has the added benefit of enabling us to relate different quantifiers, based on distributivity properties of the operators involved. A separate section discussing distributivity has, therefore, also been added. Warning! In general, the rules given in this section apply only when the range of the quantification is finite. They can all be proved by induction on the size of the range (see 12). Fortunately, in the case of universal and existential quantification, this restriction can be safely ignored. In all other cases, it is not safe to ignore the restriction. We have previously mentioned the dangers of infinite summations. An example of a meaningless quantification involving a logical operator is the (associative) equivalence of an infinite sequence of false values (denoted by

which gives, finally:

1986] DA Plaut, S Nowlan, G Hinton, Experiments on Learning by Back Propagation, Technical Report CMU-CS-86-126, Department of Computer Science, Carnegie-Mellon University, 1986 [Plutowski and White 1993] M Plutowski, H White, Selecting Concise Training Sets from Clean Data, IEEE Transactions on Neural Networks, Vol 4, No 2, March 1993, pp 305 318 [Polkowski and Skowron 1998] L Polkowski, A Skowron (eds), Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems, Springer Verlag, 1998 [Potter 1997] MA Potter, The Design and Analysis of a Computational Model of Cooperative Coevolution, PhD Thesis, George Mason University, Fairfax, Virginia, USA, 1997..

(=i:0<i:false)). It is undefined because the sequence of finite quantifications { = i : 0 ^ i < N : false) alternates between true and false and has no limit. How to handle infinite quantifications (other than universal and existential quantifications) is beyond the scope of this text.

Figure 5.4 demonstrates the principle behind the variational calculation, using the above analysis, by employing a 60 A CdTe well surrounded by 200 A Cd 0.9 Mn 0.1 Te barriers for illustration. The graph plots the total energy E as a function of the variational parameter A, for an electron in the presence of a donor at the centre of the well. The system assumes the lowest energy state possible, and hence the electron moves to a Bohr orbit of radius A=58 A, with energy E=18.366 meV.

Figure 5.7 Bohr radius A as a function of the donor position rd across the 60 A CdTe quantum well of above

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