By Pigott R., Power Ch.

Includes over 50 entries on all at present cloned and characterised cellphone adhesion molecules, together with the households of: integrins, cadherins, selectins, individuals of the immunoglobulin superfamily and different proper receptors.Provides info on: replacement nomenclature, tissue distribution and rules of expression, ligands, gene service provider and chromosomal position, protein constitution and molecular weights, amino acid series of the main ordinarily studied organisms, Pir, Swissprot and Embl/GenBank accession numbers, organic functionality, key references.

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Since (1/2) ln N > 1 already at small sample lengths (N ≥ 8), the MDL method is less prone to overfitting the data compared to the AIC. Note that first term in the MDL and AIC criterions above is simply the GLRT statistic m . Wax and Kailath [15] showed the MDL rule consistent in choosing the true dimensionality whereas the AIC tends to overestimate the dimensionality (in the large sample limit). Later [34] proved the consistency of the MDL rule when the CN assumption does not hold. 6 Conclusions In this section, we provided an overview of model order estimation methods.

In some special cases, the approximation of stochastic complexity and BIC leads to the same criterion. Detailed descriptions of the MDL method can be found in [1,4]. The MDL method does not make any assumptions on the underlying distribution of the data. In fact, it is considered to be less important since the task at hand is not to estimate the distribution that generated the data but rather to extract useful information or model from the data that facilitates by compressing it efficiently. However, codes used for compressing data and the probability mass functions are related.

2) the detection 2 . 14). Let us now derive the AIC and MDL criteria. 16) can be written compactly as n(M − m) ln (m) up to irrelevant additive constant not dependent on m. 15), we have the result that the AIC and the MDL criteria can be written in the following forms: AIC(m) = −2n(M − m) ln (m) + 2m(2M − m), MDL(m) = −2n(M − m) ln (m) + 2m(2M − m) · ln N . , the dimensionality of the signal subspace m, is found by choosing m ∈ {0, 1, . . , M − 1} that minimizes the AIC/MDL criterion above. As already pointed out, the penalty term of the MDL is (1/2) ln N times the penalty term of AIC.

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