## bbkernel

This function is not yet fully documented. This is a transcript of
the text-formatted help.

bbkernel Create a kernel for convolution.
K=bbkernel(dim,'name',par) creates a hypercube with a standard kernel.
This is an auxilliary function, mainly intended to create kernels
to use with bbconvn.
All kernels are created from a continuous function on a hyper-cube
ranging from -1 to 1 in all dimensions. By default, this is normalized
to a unit volume. However, if you give the option 'aver', the
average of each cell of the unnormalized function is used.
The function is discretized on a regular grid, with cells covering
equal volumes. Each element in K is the integral of the kernel over
a cell.
Many kernels of interest are separable, i.e. the underlying function
satisfies f(x,y,z,...)=f(x)*f(y)*f(z)*... The list specifies the
underlying unnormalized function in one dimension.
'gauss' - Gaussian kernel
Parameter: sigma (default: 1)
Function: f(x)=exp(-x^2/(2*sigma^2))
AKA: 'gaussian'
'linear' - Piecewise linear with with maximum at the origin
Function: f(x)=abs(x)
'box' - A constant
Function: f(x)=1
AKA: 'const', 'cube'
'cossqr' - Squared cosine
Function: f(x)=cos(x*pi/2)^2
The following kernel is non-separable. The argument d is the
euclidean distance from the origin.
'ball' - Solid line (1D), circle (2D), or sphere (3D and up)
Parameter: ra (default: 1)
Function: f(d)=1 for d<=ra, 0 otherwise.
AKA: 'disk', 'circle', 'pillbox', 'sphere'
'ellip' - Same as 'ball', except each semi-axis is given.
Parameter: len, vector with length of semi-axis
Function: f(p)=1 for sum((p./len).^2)<=1
AKA: 'ellipse', 'ellipsoid'
NOTE: 'ball' is only accurate for 1D and 2D. For 3D and higher, an
approximation is used for cells partly containing the ball.
See also bbconvn, (image processing toolbox)

bbinvbbkron