Developer material

Arm and MathWorks present a deep-dive into digital signal processing on Cortex-M processors. The webinar explains how to use MATLAB’s signal processing and machine learning libraries and the C code generation for DSP implementation.

Jacob Beningo, embedded software expert, demonstrates how you can use digital signal processing techniques to replace analog components to decrease bill of material costs, reduce the design cycle time and increase engineering flexibility.

DSP is an important tool for real-time embedded system engineers, critical for projects that require converting analog filter circuits into digital IIR or FIR filters. Jacob Beningo, embedded software expert, discusses how you can speed development time with the DSP software available through the Arm ecosystem, making DSP achievable in your own applications.

Arm and NXP discuss the digital signal processing co-processor in NXP’s new LPC5500 MCU series, based on the Cortex-M33 and using the co-processor interface. Hear how the combination of this interface, along with Arm software libraries, such as CMSIS-DSP and the Arm ecosystem, can help you implement a more capable processing unit for DSP tasks.

The need to decrease the BOM costs in embedded products is driven by the need for high volume, low-cost sensor systems. As IoT devices become more sophisticated, they require developers to utilize DSP to handle more features within the product, such as device provisioning. This paper examines how DSP can be used to reduce a product’s cost.

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DSP has traditionally required the use of an expensive, hard-to-program dedicated DSP processor. While microcontroller-based solutions are available using fixed-point math libraries, this requires software libraries that absorb more processing cycles than a processor that is capable of executing DSP instructions. This paper explores how you can speed up DSP codecs using the DSP extensions built into the Arm Cortex-M processors.

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Data-over-sound technology presents a compelling solution for many device-to-device connectivity applications, particularly for use cases that require frictionless, low-cost connectivity with nearby devices. Read this white paper to understand the fundamental concepts and benefits of data-over-sound connectivity and how Chirp has used the digital signal processing capabilities of the Arm Cortex-M4 and Cortex-M7 processors to engineer a software-defined data-over-sound solution.

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As we see the spectacular growth in the number of autonomous, intelligent, and connected devices that are required to operate in a low-power environment, manufacturers are increasingly turning to place the Arm Cortex-M4 and Cortex-M7 processors at the heart of these devices. This white paper describes the DSP features of Cortex-M4 and Cortex-M7, and explains how they are employed in the CMSIS-DSP Library. The white paper presents some benchmark results on well-known DSP algorithms.

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Learn how to convert an analog circuit into software using Advanced Solutions Nederland’s (ASN) Filter Designer.

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Arm and MathWorks discuss how developing optimized software for Arm targets simple and scalable. This talk explores the high-level benefits of virtual platforms in Simulink and how to practically try these solutions in your framework today.

In this video you will learn how to unleash the DSP capabilities of Arm Cortex-M based microcontrollers. Using the ASN Filter Designer tool, you can generate CMSIS-DSP compliant code that can be directly imported into µVision. Enhanced features such as the Logic Analyzer display the waveforms of your input and output signals.

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This course covers basic concepts such as sampling, reconstruction and aliasing, fundamental filtering algorithms such as FIR, IIR and FFT, and software programming basics and principles for digital signal processing.

The Arm DSP textbook introduces readers to DSP fundamentals using Cortex-M based microcontrollers as demonstrator platforms. The textbook covers both theory and practice.

The DSP Education Kit teaches the theory and practice of managing digital signals that come in from a variety of sources. This is crucial, given the explosion of digital data in today’s world. While many DSP courses use software simulation packages, or expensive development kits, this course is based on low-cost, Arm-based hardware boards and Arm software licenses, allowing students to practice theory with advanced, industry-proven hardware.