CMATH is a comprehensive library for complex-number arithmetics and mathematics. The following features make CMATH an ideal replacement for other available complex class libraries: 1. High-performance implementation in machine code leads to superior speed. 2. Accuracy and safety are greatly enhanced. 3. Each of the floating-point accuracies (complex(float), complex(double), and complex(extended)) is given its own, individually optimized treatment. 4. Polar coordinates (magnitude;angle) are supported in addition to the usual cartesian coordinates (real;imaginary). 5. Switching from your compiler's complex class library to CMATH is very simple: Just replace the include-file <complex.h> with <newcplx.h> - that's it! This version is for the Embarcadero / Borland C/C++ compiler series (RAD Studio, C++ Builder, BC++).

CMATH is a comprehensive library for complex-number arithmetics and mathematics. The following features make CMATH an ideal replacement for the unit Complex coming with Delphi: 1. High-performance implementation in machine code leads to superior speed. 2. Accuracy and safety are greatly enhanced. 3. Each of the floating-point accuracies (complex(float), complex(double), and complex(extended)) is given its own, individually optimized treatment. 4. Polar coordinates (magnitude;angle) are supported in addition to the usual cartesian coordinates (real;imaginary). This version contains the units for all version of Embarcadero / Borland Delphi from Delphi 7 to XE6. The 32-bit Units are for P4 (full FPU accuracy; back-compatible to Pentium and 486DX / AMD Athlon); the 64-bit Units require at least P8 (Intel Core2Duo, AMD64x2 or higher) and are available from Delphi XE2 on.

CMATH is a comprehensive library for complex-number arithmetics and mathematics. The following features make CMATH an ideal replacement for other available complex class libraries: 1. High-performance implementation in machine code leads to superior speed. 2. Accuracy and safety are greatly enhanced. 3. Each of the floating-point accuracies (complex(float), complex(double), and complex(extended)) is given its own, individually optimized treatment. 4. Polar coordinates (magnitude;angle) are supported in addition to the usual cartesian coordinates (real;imaginary). 5. Switching from your compiler's complex class library to CMATH is very simple: Just replace the include-file <complex.h> with <newcplx.h> - that's it! The Shareware edition is optimized for PentiumXX, while maintaining compatibility with AMD processors (Athlon) and down to 486DX. This version is for MS Visual C++ 5, 6, 2003, 2005, 2008, 2010, or 2012, both 32-bit and 64-bit.

CMATH is a comprehensive library for complex-number arithmetics and mathematics. The following features make CMATH an ideal replacement for the unit UComplex as well as for other available complex class libraries: 1. High-performance implementation in machine code leads to superior speed. 2. Accuracy and safety are greatly enhanced. 3. Single- and Double-precision complex functions are given their own, individually optimized treatment. 4. Polar coordinates (magnitude;angle) are supported in addition to the usual cartesian coordinates (real;imaginary).

OptiVec contains more than 3500 hand-optimized, Assembler-written functions for all floating-point and integer data types from the following fields: 1. Vectorized form of arithmetic operators and math functions. 2. Matrix operations, e.g.: multiplication, inversion, LU decomposition, singular value decomposition, eigenvalues. 3. Fast Fourier Transform techniques for efficient convolutions, correlation analyses, spectral filtering, etc., both one- and two-dimensional. 4. Curve fitting for a wide range of model functions from simple linear regression to non-linear models with multiple data sets. 5. Statistics. 6. Comparisons (e.g., as building blocks for time series analysis). 7. Analysis (derivatives, integrals, extrema, interpolation). 8. Graphical representation of data in Cartesian coordinates. 9. Complex number math, both in cartesian and polar format. The vectorized implementation in machine code makes OptiVec functions, on the average, 2-3 times faster tha...

OptiVec contains more than 3500 hand-optimized, Assembler-written functions for all floating-point and integer data types from the following fields: 1. Vectorized form of arithmetic operators and math functions. 2. Matrix operations, e.g.: multiplication, inversion, LU decomposition, singular value decomposition, Cholesky, eigenvalues. 3. Fast Fourier Transform techniques for efficient convolutions, correlation analyses, spectral filtering, etc., both one- and two-dimensional. 4. Curve fitting for a wide range of model functions from simple linear regression to non-linear models with multiple data sets. 5. Statistics. 6. Comparisons (e.g., as building blocks for time series analysis). 7. Analysis (derivatives, integrals, extrema, interpolation). 8. Graphical representation of data in Cartesian coordinates. 9. Complex number math, both in cartesian and polar format. The vectorized implementation in Assembler makes OptiVec functions, on the average, 2-3 times fas...

OptiVec contains more than 3500 hand-optimized, Assembler-written functions for all floating-point and integer data types from the following fields: 1. Vectorized form of arithmetic operators and math functions. 2. Matrix operations, e.g.: multiplication, inversion, LU decomposition, singular value decomposition, eigenvalues. 3. Fast Fourier Transform techniques for efficient convolutions, correlation analyses, spectral filtering, etc., both one- and two-dimensional. 4. Curve fitting for a wide range of model functions from simple linear regression to non-linear models with multiple data sets. 5. Statistics. 6. Analysis (derivatives, integrals, extrema, interpolation). 7. Graphical representation of data in Cartesian coordinates. 8. Complex number math, both in cartesian and polar format. The vectorized implementation in Assembler makes OptiVec functions, on the average, 2-3 times faster than compiled source code of the same functionality. In many instances, the...

OptiVec contains more than 3500 hand-optimized, Assembler-written functions for all floating-point and integer data types from the following fields: 1. Vectorized form of arithmetic operators and math functions. 2. Matrix operations, e.g.: multiplication, inversion, LU decomposition, singular value decomposition, Cholesky, eigenvalues. 3. Fast Fourier Transform techniques for efficient convolutions, correlation analyses, spectral filtering, etc., both one- and two-dimensional. 4. Curve fitting for a wide range of model functions from simple linear regression to non-linear models with multiple data sets. 5. Statistics. 6. Comparisons (e.g., as building blocks for time series analysis). 7. Analysis (derivatives, integrals, extrema, interpolation). 8. Graphical representation of data in Cartesian coordinates. 9. Complex number math, both in cartesian and polar format. The vectorized implementation in Assembler makes OptiVec functions, on the average, 2-3 times fas...

OptiVec contains more than 3500 hand-optimized, Assembler-written functions for all floating-point and integer data types from the following fields: 1. Vectorized form of arithmetic operators and math functions. 2. Matrix operations, e.g.: multiplication, inversion, LU decomposition, singular value decomposition, eigenvalues. 3. Fast Fourier Transform techniques for efficient convolutions, correlation analyses, spectral filtering, etc., both one- and two-dimensional. 4. Curve fitting for a wide range of model functions from simple linear regression to non-linear models with multiple data sets. 5. Statistics. 6. Analysis (derivatives, integrals, extrema, interpolation). 7. Complex number math, both in cartesian and polar format. The vectorized implementation in Assembler makes OptiVec functions typically 3-5 times faster than compiled source code of the same functionality. In many instances, the numerical accuracy is improved as well. The object-oriented interfac...

OptiVec contains more than 3500 hand-optimized, machine-code-written functions for all floating-point and integer data types from the following fields: 1. Vectorized form of arithmetic operators and math functions. 2. Matrix operations, e.g.: multiplication, inversion, LU decomposition, singular value decomposition, eigenvalues. 3. Fast Fourier Transform techniques for efficient convolutions, correlation analyses, spectral filtering, etc., both one- and two-dimensional. 4. Curve fitting for a wide range of model functions from simple linear regression to non-linear models with multiple data sets. 5. Statistics. 6. Analysis (derivatives, integrals, extrema, interpolation). 7. Graphical representation of data in Cartesian coordinates. 8. Complex number math, both in cartesian and polar format. The vectorized implementation in Assembler makes OptiVec functions, on the average, 2-3 times faster than compiled source code of the same functionality. In many instances, ...