Add to ORKGComplex signal processing algorithms are specified in floating point precision. When their hardware implemen-tation requires fixed point precision, type refinement is needed. The paper presents a methodology and design en-vironment for this quantization process. The method uses independent strategies for fixing MSB and LSB weights of fixed point signals. It enables short de-sign cycles by combining the strengths of both analytical and simulation based methods.
textMany digital signal processing and communication algorithms are first simulated using floating-...
RÉSUMÉ. Les contraintes au niveau du coût, de la consommation et du temps de mise sur le marché des ...
International audienceDigital signal processing applications are implemented in embedded systems wit...
Complex signal processing algorithms are specified in floating point precision. When their hardware ...
Digital signal processing applications are specified with floating-point data types but they are usu...
International audienceThe minimization of cost, power consumption and time-to-market of DSP applicat...
This paper presents software tools that convert the C/Cµ floating point source code for a DSP algori...
This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP...
The minimization of cost, power consumption and time-to-market of DSP applications requires the deve...
which permits unrestricted use, distribution, and reproduction in any medium, provided the original ...
International audienceThe minimization of cost, power consumption and time-to-market of DSP applicat...
This work proposes a floating-point to fixed-point conversion (FFC) methodology for digital VLSI sig...
International audienceMost of digital signal processing applications are specified and designed with...
The algorithms used by communication, voice and image processing systems are typically specified as ...
Author information is not shown to prevent exposure of the authors ’ identities and affiliations. In...
textMany digital signal processing and communication algorithms are first simulated using floating-...
RÉSUMÉ. Les contraintes au niveau du coût, de la consommation et du temps de mise sur le marché des ...
International audienceDigital signal processing applications are implemented in embedded systems wit...
Complex signal processing algorithms are specified in floating point precision. When their hardware ...
Digital signal processing applications are specified with floating-point data types but they are usu...
International audienceThe minimization of cost, power consumption and time-to-market of DSP applicat...
This paper presents software tools that convert the C/Cµ floating point source code for a DSP algori...
This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP...
The minimization of cost, power consumption and time-to-market of DSP applications requires the deve...
which permits unrestricted use, distribution, and reproduction in any medium, provided the original ...
International audienceThe minimization of cost, power consumption and time-to-market of DSP applicat...
This work proposes a floating-point to fixed-point conversion (FFC) methodology for digital VLSI sig...
International audienceMost of digital signal processing applications are specified and designed with...
The algorithms used by communication, voice and image processing systems are typically specified as ...
Author information is not shown to prevent exposure of the authors ’ identities and affiliations. In...
textMany digital signal processing and communication algorithms are first simulated using floating-...
RÉSUMÉ. Les contraintes au niveau du coût, de la consommation et du temps de mise sur le marché des ...
International audienceDigital signal processing applications are implemented in embedded systems wit...