Low-cost didactic platform for real-time adaptive filtering: Application on noise cancellation

Abstract

Didactic platforms, used in real-time digital signal processing courses, are generally dedicated digital signal processors or field-programmable gate arrays. These devices are expensive and difficult to program, preventing their widespread use in signal processing courses. On the other hand, the new technology of digital signal controllers, microcontrollers with floating point and mathematical operations, can reduce the cost of dedicated platforms for real-time digital signal processors, facilitating the development of digital signal processors projects and educational applications, such as teaching adaptive filters. Here, we present a low-cost didactic platform for developing real-time adaptive filters using the digital signal processors hardware based on the ARM Cortex-M7 processor. We present the theoretical aspects of the least mean squares and normalized least mean squares algorithms and an experimental script to help students learn real-time adaptive filters. We also describe the platform structure and the performance measurement, in terms of mean square error, signal-to-noise ratio, and computational efficiency. Finally, we present a brief discussion on the use of this platform in classes and the improvement in the student engagement and attendance.

Analysis Of The Effect Filter Order Number On Noise Canceller System Using STM32F4

“…These noise signals may affect the quality of signal reception and reproduction of the transmitted signal. Noise can also limit the system's range at a certain transmit power, affect the sensitivity of the reception signal, and cause a reduction in system bandwidth [4]. Noise in the radio receiver might generate an obnoxious hissing sound in the speakers.…”

“…An adaptive filter is a filter that alters the coefficients to adapt to changes in signal statistics to optimize the signal from distortion. The Least Mean Square (LMS) algorithm, which may be applied to the Finite Impulse Response (FIR) adaptive filter, is one of the most commonly used adaptive filter algorithms [4]. One of the techniques that can be used to change a digital filter's coefficients is the Least Mean Square (LMS) approach.…”