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Digital Signal Processing

Digital Signal Processing

More advanced product designs often include realtime digital signal processing capabilities. The team at Spark Product Innovation has experience designing and implementing algorithms for many different product applications typically where an incoming digital data stream is processed in the time, space or frequency domain to extract pertinent information from a system.

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DSP Applications

DSP applications where we have experience include:

• audio and speech signal processing
• real world sensing such as SONAR, RADAR or LIDAR.
• Image processing
• Data compression & encryption
• Complex control operations
• Object tracking
• Financial trend analysis
• Seismic data processing.

The Spark Product Innovation workflow makes extensive use of Matlab and Simulink models, allowing fixed or floating point analysis of the algorithm and taking advantage of automatic generation of code for rapid prototyping and implementation of DSP algorithms in DSP processor, GPU or FPGA platforms.



DSP Processors

The Spark Product Innovation team have implemented DSP algorithms on Analog SHARC and TI C6000 series processors including the multi core C6678 processor. We know how to interface to high speed ADC’s and other peripherals for the fast and efficient processing of data.


FPGA

FPGA’s are an established choice for low power, reliable parallel processing for DSP applications, particularly suited to “multiply & add” type algorithms such as IIR and FIR filtering of digital signals. The Spark Product Innovation team can analyse your DSP requirements, and design the FPGA solution that fits your products cost and power requirements.


GPU

We have seen an increasing trend to use GPU’s for parallel realtime processing and analysis of digital data flows where power requirements are not a restriction. Spark Product Innovation have experience with the Nvidia tesla GPU range and design of multiple stream digital signal processing using the CUDA library in C/C++ as well as some of the other widely available GPU libraries such as cuBLAS, cuFFT, NPP etc.



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