affine combination造句

• One says also that g is an "'affine combination "'of the a _ i with coefficients \ lambda _ i.
• The difference space can be identified with the set of " formal differences ", modulo the relation that formal differences respect affine combinations in an obvious way.
• The affine span of is the set of all ( finite ) affine combinations of points of, and its direction is the linear span of the for and in.
• In other words, the only " well-behaved " centers which satisfy Archimedes'Lemma are the affine combinations of the circumcenter of mass and center of mass.
• *PM : approximate non-linear transformation of affine combination, id = 9088 new !-- WP guess : approximate non-linear transformation of affine combination-- Status:
• *PM : approximate non-linear transformation of affine combination, id = 9088 new !-- WP guess : approximate non-linear transformation of affine combination-- Status:
• Similarly, one can consider affine combinations, conical combinations, and convex combinations to correspond to the sub-operads where the terms sum to 1, the terms are all non-negative, or both, respectively.
• Thus the predicted class is an affine combination of the classes of every other point, weighted by the softmax function for each j \ in C _ j where C _ j is now the entire transformed data set.
• While Alice knows the " linear structure ", both Alice and Bob know the " affine structure "  i . e . the values of affine combinations, defined as linear combinations in which the sum of the coefficients is 1.
• When a stochastic matrix,, acts on a column vector, " " ", the result is a column vector whose entries are affine combinations of " " " with coefficients from the rows in.
• Linear and affine combinations can be defined over any field ( or ring ), but conical and convex combination require a notion of " positive ", and hence can only be defined over an ordered field ( or ordered ring ), generally the real numbers.
• The dual vector space of is naturally isomorphic to an ( " n " + 1 )-dimensional vector space which is the free vector space on "'A "'modulo the relation that affine combination in "'A "'agrees with affine combination in.
• The dual vector space of is naturally isomorphic to an ( " n " + 1 )-dimensional vector space which is the free vector space on "'A "'modulo the relation that affine combination in "'A "'agrees with affine combination in.
• If, on the other hand, the kernel assumes negative values, such as the sinc function, then the value of the filtered signal will instead be an affine combination of the input values, and may fall outside of the minimum and maximum of the input signal, resulting in undershoot and overshoot.
• These concepts often arise when one can take certain linear combinations of objects, but not any : for example, probability distributions are closed under convex combination ( they form a convex set ), but not conical or affine combinations ( or linear ), and positive measures are closed under conical combination but not affine or linear  hence one defines signed measures as the linear closure.