Introduction | Moving Average Filters | FIR Filters | Code and data | IIR Filters | Transfer Functions |
Digital filters typically have one input and one output. A digital signal is applied to the input and a modified digital signal is produced at the output. A digital signal is basically a stream of numbers, usually spaced evenly in time.
Typically the signal is modified in some frequency dependent way, so that wanted frequencies are retained and unwanted frequencies are removed.
They are used to process signals in the fields of audio, speech, image and video processing, radar, sonar, ultra-sonics, communications, modulation and demodulation, sensors, motor control, power management, sensor arrays, medical, automotive, aviation, aero-space, hi-fi, cell-phones, audio effects, appliances and many, many more. Anywhere that a computer meets a sensor or signal is a candidate for a digital filter.
They are typically used on personal computers, micro-processors, micro-controllers, digital signal processors (DSPs) and controllers (DSCs), field-programmable gate arrays (FPGAs) and application-specific integrated circuit (ASICs).
MicroModeler DSP is a digital filter editor. You choose from a variety of digital filters from the menu-bar and drag them to your application. You then use the handles and controls to interactively adjust the filter's response while viewing the various graphs and curves. Code, coefficients and test cases are automatically generated which you then copy and paste into your project. In your application, you create an instance of the filter, write a stream of numbers into its input and read a stream of numbers from its output.
Digital filters are typically one software component in a larger system and the goal of MicroModeler DSP is to make the design, coding and testing of these components as straightforward and as cost effective as possible. We hope to be able to remove the steep learning curves, thick books filled with equations and long, iterative development cycles often associated with digital filter development and provide a system that is robust, fast to learn and use and produces excellent quality results in minutes instead of weeks.
MicroModeler DSP is designed for engineers, programmers and scientists, who have a need to process data in some frequency dependent way. The ability to quickly design integer filters and automatically generate efficient filter code make it very suitable for embedded systems developers.
Traditionally, electronic signals were processed using analog components such as inductors, capacitors, transistors, op-amps and active filters. In today's digital age, these signals are becoming more frequently processed by digital elements such as computers, microprocessors and FPGAs. Digital Signal Processing involves the application of digital elements to the processing of electronic signals.
The advantages of digital over analog signal processing are:In the next section, we will introduce you to a simple digital filter (the moving average filter) and how to create it in MicroModeler DSP. We will then take the concept of the moving average filter and extend it to the more general case of the FIR filter.
Introduction | Moving Average Filters | FIR Filters | Code and data | IIR Filters | Transfer Functions |