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1 3: Iteration This is clearly true (since k ^ N and k ^ N together imply that k = N). The requirement (13.11) checks the initialization. We have to verify that { (KAf } fe,5 := 0,0 { O^k^N A s = Using the assignment axiom, this follows from A 0= ( Z i : 0 ^ i < which is true by the empty-range rule for summations. The requirement (13.12) checks the loop body. We have to verify that A 5 = ( Z i : 0 < i < f e : a [ i ] ) A k<N k,s := k+l,s+a[k] { O ^ f c ^ J V A 5 = ( I i : 0 ^ i < k : a [ i ] > A N~k<C } . Again, use of the assignment axiom is called for. We get A 5 = <Ii:(Ki<fc:a[i]) A k<N A N-k = C A s+a[k] = ( S i : 0 ^ i < f e + l : a[i]> A N-(k+l)<C . This is true by virtue of the splitting and one-point rules for summation (and simple arithmetic). The final condition (13.10) is clearly satisfied: A 5 = (Si:0^i< A N-k = C }

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A different technique of weight initialization is due to Su et a/., where the objective is to define a large enough hyper cube to cover all the training patterns [Su et al. 1999]. The algorithm starts by finding the four extreme points of the map by determining the four extreme training patterns. Firstly, two patterns are found with the largest inter-pattern Euclidean distance. A third pattern is located at the furthest point from these two patterns, and the fourth pattern with largest Euclidean distance from these three patterns. These four patterns form the corners of the map. Weight values of the remaining neurons are found through interpolation of the four selected patterns, in the following way: Weights of boundary neurons are initialized as

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The mathematical form of this implies that, as a minimum, w(z} must be continuous. If it is not, then the first derivative will contain poles which must be avoided if the system is to have finite values for the kinetic energy. Given that w ( z ) has already been deduced as zero outside of the well, then w(z} within the well must be zero at both edges too.

Evaluating a polynomial involves a more complicated summation and is the basis of several other algorithms. Suppose we are required to evaluate

If the origin is taken as the left hand edge of the well as in Fig. 2.2, then w ( z ) as defined in equation (2.8) can contain no cosine terms, i.e. B = 0, and hence w(z) = Asin kz. In addition, for w(0) = w(l w ) = 0:

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for given real number X and array a. It is possible, of course, to regard this problem as a specific instance of the summation problem just discussed. Doing so means the introduction of variables 5 and k satisfying the invariant property A 5 = <Zi:0^i< The problem is that each iteration of the loop body involves executing the assignment k,5 := fc+1 ,s + a[k]xXk and thus evaluating Xk.

j-n + di,

where n is an integer, representing a series of solutions. Substituting into equation (2.9), then the energy of the confined states is given by:

An alternative method, called Homer's rule, is preferable because it uses fewer multiplications. Homer's rule involves computing the values

The only remaining unknown is the constant factor A, which is deduced by considering the normalisation of the wave function; as w* ( z ) w ( z ) represents the probability of finding the particle at a point z, then as the particle must exist somewhere:

+ a[N-3] ,

'Wl"-(j-l) + J -

Under the effective mass and envelope function approximations, the energy of an electron or hole in a hypothetical infinitely deep semiconductor quantum well can be calculated by using the effective mass m* for the particle mass m of equation (2.13).

k,s := JV.O ,

Figure 2.3 First three energy levels versus well width for an electron in a GaAs infinite potential well

for all j = 2, , J - 1 and k = 2, , K - 1. The remaining codebook vectors are initialized as

k=0 .

Figure 2.3 displays the results of calculations of the lowest three energy states of an electron in a GaAs well of width lw surrounded by hypothetical infinite barriers (for these and all material parameters see Appendix A). All three states show the same monotonic behaviour, with the energy decreasing as the well width increases. The sine function solutions derived for this system are completely standard and found extensively in the literature. Although it should be noted that the arguments developed for setting the boundary conditions, i.e. w(z) continuous, also implied that the first derivative should be continuous too, although use is never made of this second boundary condition. The limitations of solution imposed by this are avoided by saying

k,s := AT.O ;

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