bilinear

A bilinear form can be defined on A in the sense of the previous example.

The operation is a bilinear map; but no other conditions are applied to it.

Such an inner product will be bilinear: that is, linear in each argument.

These three numbers form the signature of the bilinear form.

The bilinear nature of the problem is effectively used in an alternative approach, called variable projections.

We consider here the solution theory for bilinear equations in integers.

One can introduce a bilinear product on as follows.

A vector space with a bilinear form generalizes the case of an inner product.

This will be the case if B is a symmetric or skew-symmetric bilinear form.

The bilinear form uses gradient of the functions that has only 1st order differentiation.

A bilinear form on D arises by pairing the image distribution with a test function.

This notation emphasizes the bilinear character of the form.

There may be non-bilinear maps whose alternatization is also bilinear.

When α is the identity, then f is a bilinear form.

A common approach for learning similarity, is to model the similarity function as a bilinear form.

This bilinear form then transform tensorially under a reflection or a rotation.

When the bilinear form applied to two vectors results in zero, then they are orthogonal.

This bilinear form is called the Frobenius form of the algebra.

In mathematics, an algebra over a field is a vector space equipped with a bilinear product.

The above expression, a symmetric bilinear form at each point, is the second fundamental form.

However, it is still highly angle-dependent and the driver sometimes forces bilinear filtering for speed.

The bilinear map associates a quantity to the dual base vectors.

A multilinear map of two variables is a bilinear map.

We form a bilinear form using only the assumed function (not even the gradient).

Lattices are often embedded in a real vector space with a symmetric bilinear form.