extremum

Let be a function and suppose that is a local extremum of .

The general theory of extremum estimators was developed by .

(This is not the same as saying that y is at an extremum).

On the other hand, convergence (even to a local extremum) is not guaranteed when using this method in isolation.

Note that while is a critical point of , it is not a local extremum.

The table below shows the absence of impact of the price extremum over consumption.

The theory of extremum estimators does not specify what the objective function should be.

A pixel receives a score when it represent an extremum of all the projections.

With real data, EM also is subject to the usual local extremum traps.

It is seen that the energy is at an extremum at equilibrium.

Note that if happens to be a quadratic function, then the exact extremum is found in one step.

Most of the energy distribution theorems and extremum principles in network theory can be derived from it.

A local extremum with extent defined in this way was referred to as a grey-level blob.

Togther they are known as the extrema (singular: extremum).

If is a global extremum of f, then one of the following is true:

Some of these parameters require the measurement of the exact position of the extremum.

Real time optimization by extremum seeking control.

If or are computed to be less than zero, then the input data points are not strictly monotone, and is a local extremum.

The new approach calculates the interpolated location of the extremum, which substantially improves matching and stability.

If the offset is larger than in any dimension, then that's an indication that the extremum lies closer to another candidate keypoint.

Otherwise the offset is added to its candidate keypoint to get the interpolated estimate for the location of the extremum.

A strong extremum is also a weak extremum, but the converse may not hold.

If the characteristic values deviate from an extremum, the parameters need to be varied until optimum values are found.

Paltridge (1978) cited Busse's (1967) fluid mechanical work concerning an extremum principle.

Only function values are used, and when this method converges to an extremum, it does so with a rate of convergence of approximately 1.324.