Data input array, specified as a positive scalar, vector, matrix,
or multidimensional array of fixed-point or built-in data types. When
the input array contains values between 0.5 and 2, the algorithm is
most accurate. A pre- and post-normalization process is performed
on input values outside of this range. For more information on this
process, see Pre- and Post-Normalization.

The number of iterations that the CORDIC algorithm performs,
specified as a positive, integer-valued scalar. If you do not specify niters,
the algorithm uses a default value. For fixed-point inputs, the default
value of niters is u.WordLength - 1.
For floating-point inputs, the default value of niters is
52 for double precision; 23 for single precision.

Specify optional comma-separated pairs of Name,Value arguments.
Name is the argument
name and Value is the corresponding
value. Name must appear
inside single quotes (' ').
You can specify several name and value pair
arguments in any order as Name1,Value1,...,NameN,ValueN.

Boolean value that specifies whether to scale the output by
the inverse CORDIC gain factor. If you set ScaleOutput to true or 1,
the output values are multiplied by a constant, which incurs extra
computations. If you set ScaleOutput to false or 0,
the output is not scaled.

CORDIC is an acronym for COordinate Rotation
DIgital Computer. The Givens rotation-based CORDIC algorithm is one
of the most hardware-efficient algorithms available because it requires
only iterative shift-add operations (see References). The CORDIC algorithm
eliminates the need for explicit multipliers. Using CORDIC, you can
calculate various functions, such as sine, cosine, arc sine, arc cosine,
arc tangent, and vector magnitude. You can also use this algorithm
for divide, square root, hyperbolic, and logarithmic functions.

Increasing the number of CORDIC iterations can produce more
accurate results,
but doing so also increases the expense of the computation and adds
latency.

X is initialized to u'+.25,
and Y is initialized to u'-.25,
where u' is the normalized function input.

With repeated iterations of the CORDIC hyperbolic kernel, X approaches $${A}_{N}\sqrt{u\text{'}}$$,
where A_{N} represents the
CORDIC gain. Y approaches 0.

Pre- and Post-Normalization

For input values outside of the range of [0.5, 2) a pre- and
post-normalization process occurs. This process performs bitshifts
on the input array before passing it to the CORDIC kernel. The result
is then shifted back into the correct output range during the post-normalization
stage. For more details on this process see "Overcoming Algorithm
Input Range Limitations" in Compute Square Root Using CORDIC.

fimath Propagation Rules

CORDIC functions discard any local fimath attached
to the input.

The CORDIC functions use their own internal fimath when
performing calculations:

OverflowAction—Wrap

RoundingMethod—Floor

The output has no attached fimath.

References

[1] Volder, JE. "The CORDIC Trigonometric
Computing Technique." IRE Transactions on Electronic
Computers. Vol. EC-8, September 1959, pp. 330–334.

[2] Andraka, R. "A survey of CORDIC
algorithm for FPGA based computers." Proceedings
of the 1998 ACM/SIGDA sixth international symposium on Field programmable
gate arrays. Feb. 22–24, 1998, pp. 191–200.

[3] Walther, J.S. "A Unified Algorithm
for Elementary Functions." Hewlett-Packard Company, Palo Alto.
Spring Joint Computer Conference, 1971, pp. 379–386. (from
the collection of the Computer History Museum). www.computer.org/csdl/proceedings/afips/1971/5077/00/50770379.pdf

[4] Schelin, Charles W. "Calculator Function
Approximation." The American Mathematical Monthly.
Vol. 90, No. 5, May 1983, pp. 317–325.