The phrase "a finite expression" is correct and usable in written English.
It can be used in contexts related to mathematics, computer science, or logic, where it refers to an expression that has a limited or fixed value.
Example: "In calculus, we often analyze a finite expression to determine its limit as it approaches a certain value."
Alternatives: "a bounded expression" or "a limited expression".
The adjoint equations are validated by means of a comparison between the adjoint solution and a finite difference expression.
In my humble apprehension, unless there be some such clear and finite expression, this clause now under consideration will go to any thing our rulers may think proper.
In base 10, for example, only numbers with factors of 2 and 5 (e.g., 8 or 50) are regular, and the reciprocals (1/8 = 0.125, 1/50 = 0.02) have finite expressions; but the reciprocals of other numbers (such as 3 and 7) repeat infinitely and, respectively, where the bar indicates the digits that continually repeat).
Thereby the goal is to obtain finite expressions in terms of known functions like elementary, Liouvillian or special functions that annihilate the given differential equation upon substitution; they exist only in exceptional cases.
Note that in a finite case, although the expression of U will be changed, the main predictions about a2, b2, γ in the previous section do not change.
Let M be a microarray dataset, i.e. the measurements space, which can be defined as: M = (C, G, L, Class) where C ={1, 2,… n} is a finite set of gene expression samples, G={1, 2,… m} is a finite set of genes, Class={ c1, c2,… c p } is a finite set of clinical categories.
First, we obtain an explicit expression (at the continuous level) of the expected compliance and its variance, then we consider a numerical discretization (by using a finite element method) of this expression and finally we use an optimization algorithm.
On the contrary, if x∞>0 (chaotic regime), the initial perturbation of even a small fraction of genes propagates across the entire system, finally altering the expression of a finite fraction x∞ of genes in the genome.
A prime virtue of RTM is how readily it accommodates productivity and systematicity: Productivity: RTM postulates a finite set of primitive Mentalese expressions, combinable into a potential infinity of complex Mentalese expressions.
Our modelling approach involves the discretization and digitization of temporal mRNA expression profiles into a finite number of levels (states), which are defined by discretization of continuous/analogue gene expression levels (Step 1 & 2, Figure 2 and Methods).
