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"The most comprehensive treatment of FFTs to date. Van Loan captures the interplay between mathematics and the design of effective numerical algorithms--a critical connection as more advanced machines become available. A stylized Matlab notation, which is familiar to those engaged in high-performance computing, is used. The Fast Fourier Transform (FFT) family of algorithms has revolutionized many areas of scientific computation. The FFT is one of the most widely used algorithms in science and engineering, with applications in almost every discipline. This volume is essential for professionals interested in linear algebra as well as those working with numerical methods. The FFT is also a great vehicle for teaching key aspects of scientific computing."

"The DFT: An Owner's Manual for the Discrete Fourier Transform explores both the practical and theoretical aspects of the DFT, one of the most widely used tools in science, engineering, and computational mathematics. Designed to be accessible to an audience with diverse interests and mathematical backgrounds, the book is written in an informal style and is supported by many examples, figures, and problems.Conceived as an "owner's" manual, this comprehensive book covers such topics as the history of the DFT, derivations and properties of the DFT, comprehensive error analysis, issues concerning the implementation of the DFT in one and several dimensions, symmetric DFTs, a sample of DFT applications, and an overview of the FFT."

"Algoritma Transformasi Fourier Cepat (TFG) merupakan salah satu algoritma yang menerapkan metoda paralel untuk mencari Transformasi Fourier Diskrit (TFD). TFD dari sebuah vektor x berdimensi n dengan metoda sekuensial dapat dihitung dalam 0{n^) tetapi dengan algoritma TFC dapat diturunkan menjadi 0(log n). Dalam tugas akhir ini akan menjelaskan Algxiritma Transformasi Fourier Cepat dalam perkalian polinomial, yang masing-masing berderajat n-1 dan m-1. Kesimpulan yang diperoleh dari penjelasan tersebut adalah jumlah operasi untuk mencari perkalian polinomial dengan algoritma TFC sebesar 0{{n+m)\og{n+m)) dibandingkan dengan sekuensial sebesar 0{nm) namun waktu pelaksanaannya sama."