Adaptive architecture

Neuronal networks are nowadays predominantly applied in classification tasks. Here, three kind of networks are tested First the backpropagation network is used, due to the fact that it is the most robust and common network. The other two networks which are considered within this study have special adapted architectures for classification tasks. The Learning Vector Quantization (LVQ) Network consists of a neuronal structure that represents the LVQ learning strategy. The Fuzzy Adaptive Resonance Theory (Fuzzy-ART) network is a sophisticated network with a very complex structure but a high performance on classification tasks. Overviews on this extensive subject are given in [2] and [6]. 

However, to check the forming behaviour of 3D warp interlock made with commingled yams, using such a complex final preform as represented in Figure 10.6, a first approach is applied on different fabric parameters and forming shapes to find the best adapted architecture to the stamping process. 

Bell, A. D. and Tomlinson, P. B. (1980) Adaptive architecture in rhizomatous plants. Botanical Journal of the Linnean Society, 80 125-160. 

Hardware problems as the instruments have rather poor processors and custom architecture, it is difficult to test new configurations and, once the new configuration is selected, it is often necessary to strongly modify the hardware in order to adapt the existing instruments. 

Rather than making this statement, one should consider first whether the representation of the Y-variablc is appropriate. What wc did here was to take categorical information as a quantitative value. So if wc have, for instance, a vector of class 1 and one of c lass 9 falling into the same neuron, the weights of the output layer will be adapted to a value between 1 and 9, which docs not make much sense. Thus, it is necessary to choose another representation with one layer for each biological activity. The architecture of such a counter-propagation network is shown in Figure 10.1 -11. Each of the nine layers in the output block corresponds to a different MOA. 

FIGURE 22.20 The molecular architecture of PSI. PsaA and PsaB constitute the reaction center dimer, an integral membrane complex P700 is located at the lumenal side of this dimer. PsaC, which bears Fe-S centers and Fb, and PsaD, the interaction site for ferre-doxin, are on the stromal side of the thylakoid membrane. PsaF, which provides the plasto-cyaiiin interaction site, is on the lumenal side. (Adapted from Golbeck, J. H., 1992. Amiual Review of Plant Physiology and. Plant Molecular Biology 43 293-324.)... 

No single ART2 equation or set of equations provides the desired adaptive properties for the system. Rather, it is the synergistic effect of this architecture as a whole that gives rise to these properties. A description of the ART network applied to process situations can be found in Whiteley and Davis (1996) a complete description of an ART network can be found in Carpenter and Grossberg (1987a). 

Both cases can be dealt with both by supervised and unsupervised variants of networks. The architecture and the training of supervised networks for spectra interpretation is similar to that used for calibration. The input vector consists in a set of spectral features yt(Zj) (e.g., intensities at selected wavelengths zi). The output vector contains information on the presence and absence of certain structure elements and groups fixed by learning rules (Fig. 8.24). Various types of ANN models may be used for spectra interpretation, viz mainly such as Adaptive Bidirectional Associative Memory (BAM) and Backpropagation Networks (BPN). The correlation... 

Figure 88 The supramolecular architectures (171) assembled by the C—H S—H H—B hydrogen/dihydrogen-bond interactions between mercaptane and metallacarborane complexes. (Adapted from ref. 167.)...

Feedback provided by on-line monitoring of self-assembling processes will play an increasingly important role in controlling the microscopic and macroscopic architecture of molecular assemblies. Successful adaptation of char-... 

Soft and topologically adaptable supramolecular modules that allow host lattices to achieve dense packing through low-energy deformations, while retaining their inherent dimensionality and supramolecular connectivity, can facilitate the systematic design of molecular inclusion compounds. This is demonstrated by the ability to predict and maintain architectural control in a series of lamellar host frameworks. 

Some of the early work on systematic description of software architecture was done by Shaw and Garlan [Shaw96b]. A good description of the breadth of issues involved in software architecture, which we have used and adapted, is in [Bass98], Our informal definition of architecture was coined in frustration by D Souza (we believe). 

Entities resulting from self-assembly and self-organization of a number of components may undergo self-correction and adaptation. This might also explain why large multisite protein architectures are formed by the association of several smaller protein subunits rather than from a single long polypeptide. 

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