This paper presents a method to improve the calculation of functions which specially demand a great amount of computing resources. The method is based on the choice of a weighted primitive which enables the calculation of function values under the scope of a recursive operation. When tackling the design level, the method shows suitable for developing a processor which achieves a satisfying trade-off between time delay, area costs, and stability. The method is particularly suitable for the mathematical transforms used in signal processing applications. A generic calculation scheme is developed for the discrete fast Fourier transform (DFT) and then applied to other integral transforms such as the discrete Hartley transform (DHT), the discrete cosine transform (DCT), and the discrete sine transform (DST). Some comparisons with other well-known proposals are also provided.