The Fundamental Open Hypermedia Model (FOHM) is an alternative approach to Generalised Hypertext that views the various Hypertext domains as continuous rather than discrete.
Here each contribution is often an atom in a much larger cloud and the publication process is continuous rather than discrete.
In effect, speakers pronounce two or more phonemes at a time, and transitions are fluid rather than discrete (see, e.g., Liberman 1970, 309, fig. 5, Diehl et al. 2004).
Here the eigenvalues are assumed to be discrete, but the set of eigenvalues of an observable may be continuous rather than discrete.
In reality, gene expression levels reflected by microarray data tend to be continuous rather than discrete.
The output vector would therefore be expected to be composed of elements that are continuous rather than discrete.
The attachment-related avoidance and anxiety subscales are continuous dimensions rather than discrete attachment types (Fraley and Waller 1998).
Finally, we note that our method can be applied to problems in which the entries in g are continuous rather than discrete.
Traditional linear model [ 9] defined in Equation (1) is based on the fact that gene expression levels tend to be continuous rather than discrete.
Here a different approach is used, where the absolute gene expression data are used to create continuous, rather than discrete, reaction weightings.
However, gene expression levels tend to be continuous rather than discrete, and discretization can lend to a large loss of information.
