If you are using digital signal processing techniques, these resources from Arm and partners can help. They include digital signal processing on Arm-based Cortex-M platforms and the optimized CMSIS-DSP library for building power-efficient and performant IoT applications. Go to section:

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Digital signal processing with CMSIS-DSP library

Implement classical ML techniques like Support Vector Machines (SVMs) with functions in the CMSIS-DSP software library.

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Use the CMSIS-DSP Python wrapper and learn how the CMSIS-DSP API is represented in Python.

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Use Advanced Solutions Nederland (ASN) filter designer to generate code that is compliant with CMSIS-DSP and imported into µVision.

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Run DSP algorithms on Cortex-M processors using software including the CMSIS-DSP library.

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Arm and MathWorks: DSP software masterclass

Use MATLAB’s signal processing and machine learning libraries for Cortex-M based devices.

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Developing with the NXP LPC5500 MCU series

See how the combination of the DSP coprocessor offered with the LPC5500 MCU series and the CMSIS-DSP library can provide a more capable processing unit for DSP tasks.

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Improving Codec Execution using Cortex-M

Speed up DSP codecs using the DSP extensions built into Cortex-M processors.

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Reduce BOM costs with digital signal processing

Convert analog circuits to software using modelling software such as MathWorks MATLAB to reduce design cycle time and bill of material costs.

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Read paper

Design an FIR filter

Design a linear phase DSP application with Python, for a system that does not require a feedback component, using the Mbed DSP API.

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Software and tools

Arm Keil MDK

Keil MDK includes Arm Compiler, IDE, debugger and middleware. Use Keil MDK for Cortex-M based applications.

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CMSIS-DSP software library

Free software library of common signal processing and mathematical functions optimized for Cortex-M processors.

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DSP ecosystem partners

DSP software packages from Arm DSP ecosystem partners for audio codecs, video and speech codecs, and audio enhancement algorithms.

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Get started with DSP resources

If you are new to DSP, these resources will help you understand the fundamentals. This course and textbook covers basic concepts such as sampling, reconstruction and aliasing, fundamental filtering algorithms such as FIR, IIR and FFT, and software programming basics.

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