More than 90 percent of signal-processing systems use finite-precision (fixed-point) arithmetic. This is because fixed-point hardware is lower cost and lower power, and often higher speed than floating-point hardware. The advantage of fixed-point hardware in a digital signal processing (DSP) microprocessor ( P) is largely due to the reduced data word size, since fixed-point is practical with 16 bit data, while floating-point usually requires 32 bit data. Field programmable gate arrays (FPGAs) gain similar advantages from fixed-point data word length and have the additional advantage of being customizable to virtually any desired word length. Unfortunately, most academic coursework ignores the unique challenges of fixed-point algorithm design. This text is intended to fill that gap by providing a solid introduction to fixed-point algorithm design. Readers will see both the theory and the application of the theory to useful algorithms.This book is intended to fill the gap between the aideal precisiona digital signal processing (DSP) that is widely taught, and the limited precision implementation ... There are a number of simple exercises integrated into the text to allow you to test your understanding. Answers to the exercises are included in the footnotes.
|Title||:||Fixed-Point Signal Processing|
|Author||:||Wayne T. Padgett, David V. Anderson|
|Publisher||:||Morgan & Claypool Publishers - 2009|