Early testing and validation of control algorithms are indispensable for the development of new audio signal processing electronics. Tight cost and time targets are usually significant drivers. Real-time simulation and testing enable you to design and validate more rapidly, avoiding laborious hardware development and DSP coding at early stages. Discover how real-time simulation is applied to complex open and closed-loop signal control, such as active noise canceling, acoustic feedback cancellation, electroacoustic absorbers, predictive maintenance, and audio classification.
Analog audio IO modules with high signal-to-noise (SNR) ratios and fast sampling frequencies allow you to connect your audio devices directly to the real-time target machine. Also, benefit from digital audio interface solutions supporting AES/EBU and S/PDIF standards.
The main benefits of the Speedgoat and MathWorks® real-time simulation and testing platform for audio signal processing applications are:
“The Speedgoat real-time target machine was selected because of its widespread use in the hearing instruments industry." "I am impressed by the relatively short time required to convert the MATLAB® code into a running real-time implementation. "Being able to demonstrate algorithms in real-time adds a lot of credibility to our research endeavour.” Prof. Dr. - Ing. Rainer Martin, ICanHear Coordinator
“The Speedgoat real-time target machine was selected because of its widespread use in the hearing instruments industry."
"I am impressed by the relatively short time required to convert the MATLAB® code into a running real-time implementation.
"Being able to demonstrate algorithms in real-time adds a lot of credibility to our research endeavour.”
Prof. Dr. - Ing. Rainer Martin, ICanHear Coordinator
Improve the infotainment system's sound experience using active noise canceling (ANC) to reduce structure- and air-borne noise in cars. Rapidly prototyping controls with Speedgoat hardware allows you to develop and validate your new ANC algorithm on a single platform. Eliminate thereby time-consuming and resource-intensive code porting and debugging. Test your new control by connecting accelerometers, microphones, and speakers to the real-time system. Mobile real-time computers allow easy testing in the car for more realistic filter parameter tuning and optimizing sensor positions.
Frequently Used I/O Interfaces
Simulink® Application Resources
Leverage real-time simulation and testing to improve closed-loop ASAC algorithm designs for active reduction of noise transmission into aircraft cabins. Interface the real-time target computer to sensors and inertial exciters to test active vibration damping of airplane trim panels. Use rapid prototyping to determine the control parameters of sensor-actuator or self-sensing actuator systems. Measure transfer functions and calculate the optimal active damping for structural vibrations.
Use automatic code generation for real-time prototyping of adaptive digital filters for feedforward or closed-loop ANC in headphones. Take advantage of high-resolution audio IO modules with a high signal-to-noise ratio (SNR) for open-loop, feedforward control loops, and very-fast, low-latency IO modules for closed-loop ANC. FPGA modules facilitate even lower latencies for your highest-fidelity closed-loop algorithms.
Evaluate and optimize noise reduction algorithms for hearing aids in real-time using efficient rapid control prototyping rather than laborious DSP coding. Model your new ideas swiftly in Simulink® using fast Fourier transform (FFT), inverse FFT, and other functions from the Simulink® library. Deploy your control seamlessly to the real-time target with automated code generation. Application targeted IO modules allow you to connect microphones, speakers, and third-party signal processing hardware to the real-time target.
Design and validate adaptive finite input response (FIR) filters in AFC loops to eliminate acoustic feedback in speech and audio using real-time signal processing. Fast-sampling A/D conversion combined with direct memory access (DMA) or low-latency FPGA signal processing enables you to control high-fidelity closed-loops for AFC applications.
Real-time simulation and testing combined with model-based design accelerate the development of your next-generation home and concert audio system. Take advantage of real-time simulation hardware, which is fully integrated into the MATLAB® and Simulink® workflow. Develop control algorithms for novel electroacoustic absorber concepts to achieve effective sound absorption of standing waves in the room.
Reduce costly downtime in production through predictive maintenance of machinery based on acoustic condition monitoring. Real-time simulation enables you to rapidly improve the processing and analysis of acoustic emissions from equipment. Effectively detect noise levels outside the normal range before material failure occurs. Leverage the integration of the real-time signal processing hardware in the Simulink®/ Simscape™ environment and easily visualize channel statistics, peak to average power ratio (PAPR), and signal space constellations.
Expedite innovation in audio classification using real-time audio and speech processing. The seamless integration of high-fidelity, real-time signal processing hardware into MATLAB® and Simulink® facilitates the straightforward design of your novel classification algorithm. Use quick feature extraction based on spectral envelope quantization and computation of log-spectral distortion and histograms. Leverage the Deep Learning Toolbox™ and Statistics and Machine Learning Toolbox™ for neural networks, machine, and deep learning.
Success Stories
Sonova - User story
Cochlear - User story
ICanHear - User story
Relevant Resources
ANC System Design for Rolling Road Noise - Presentation
ANC – From Modeling to Real-Time Prototyping - Webinar
Deploying Predictive Maintenance Algorithms to the Cloud and Edge - Technical Article
Active Noise Control with Simulink® Real-Time™ - Documentation
Rapidly prototype control designs by applying rapid control prototyping, test embedded controllers withhardware-in-the-loop simulation of digital twins, and leverage Speedgoat systems as embedded controllers.
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