Mbed waveplayer mac#
A DSP chip has a special area of hardware for processing MAC operations. It can be seen that the filter has a number of multiply and addition processes, which can be grouped into a single MAC operation. As anĮxample, if the filter taps in Figure 11.2 all have a value of 0.25, then this implements a simple mean average filter (a crude LPF) which continuously averages the last four consecutive data values. Finding the required values for the filter taps is a complex process, but many design packages exist to simplify this process. This filter is an example of a finite impulse response (FIR) filter, because it uses a finite number of input values to calculate the output value.
The order of the filter determines the steepness of the filter roll-off curve at one extreme a first order filter gives a very gentle roll-off, while at the other an eighth order is used for demanding anti-aliasing applications. The order of the filter is given by the number of delays that are used, so the example shown in Figure 11.2 is a third order filter. The values of the filter taps determine whether the filter is high pass or low pass and what the cut-off frequency is. Coefficient a2 is multiplied by the previous sample and a3 is multiplied by the sample before that. Figure 11.2 shows that coefficient a1 is multiplied by the most recent sample value. Figure 11.2 shows an example block diagram for a simple digital filtering operation.
Mbed waveplayer software#
We will not go deeply into the mathematics of digital filtering, but the software process relies heavily on addition and multiplication. The filtering can be performed with an active or a passive analog filter, but the same process can also be performed in software with a DSP operation. In general, the more complex the filter design, the steeper its roll-off can be. Filters can be designed to have different steepness of cut-off attenuation and so adjust the filter’s roll-off rate. The cut-off effect is not perfect, however, as frequencies in the stop-band are attenuated more the further away from the cut-off frequency they are. A filter 1 HP filterįigure 11.1: High-pass and low-pass filtered signalsĪn Introduction to Digital Signal Processing 221 has a cut-off frequency, which determines which signal frequencies are in the pass-band (and are still evident after the filtering) and which are in the stop-band (which are removed by the filtering operation).
We may wish to remove either the low-frequency component, by implementing a high-pass filter (HPF), or the high-frequency component, by implementing a low-pass filter (LPF). Here, there is a signal with both low-frequency and high-frequency components.
Mbed waveplayer code#
It is possible to perform DSP applications with any microprocessor or microcontroller, although specific DSP chips will outperform a standard microprocessor with respect to execution time and code size efficiency.ġ1.2 Digital Filtering Example Filters are used to remove chosen frequencies from a signal, as shown in Figure 11.1, for example. A DSP chip is therefore particularly suitable for number crunching and mathematical algorithm implementations. Hardware and associated instructions to make these operations rapid in operation and easier to code in software. Digital filtering and frequency analysis with the Fourier transform requires many numbers to be multiplied and added together, so a DSP chip provides specific internal Fast and Effective Embedded Systems Design. A DSP chip provides rapid instruction sequences, such as shift-and-add and multiply-and-add (sometimes called multiply-and-accumulate or MAC), which are commonly used in signal processing algorithms.
A digital signal processor, also informally called a DSP chip, is a special type of microprocessor used for DSP applications.
Mbed waveplayer portable#
Input and Output of Digital Data 222 Signal Reconstruction 224 Adding a Digital Low-Pass Filter 224 Adding a Push-Button Activation 228 Digital High-Pass Filter 229ġ1.4 Delay/Echo Effect 229 11.5 Working with Wave Audio Filesġ1.5.1 The Wave Information Header 233 11.5.2 Reading the Wave File Header with the mbed 235 11.5.3 Reading and Outputting Mono Wave Data 236ġ1.6 Summary on DSP 239 11.7 Mini-Project: Stereo Wave Playerġ1.7.1 Basic Stereo Wave Player 240 11.7.2 Stereo Wave Player with PC Interface 240 11.7.3 Portable Stereo Wave Player with Mobile Phone Display InterfaceĬhapter Review 241 Quiz 241 References 242ġ1.1 What is a Digital Signal Processor? Digital signal processing (DSP) refers to the computation of mathematically intensive algorithms applied to data signals, such as audio signal manipulation, video compression, data coding/decoding and digital communications. An Introduction to Digital Signal Processing Chapter Outline 11.1 What is a Digital Signal Processor? 11.2 Digital Filtering Example 220 11.3 An mbed DSP Example 222 11.3.1 11.3.2 11.3.3 11.3.4 11.3.5
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