Signal processing is now a multidisciplinary topic, used by researchers and practitioners in diverse fields, including science, engineering, medicine, finances, behavioral sciences and others.
Modern software libraries that include dedicated languages and packages are now readily available, dramatically simplifying the development and application of signal processing techniques. The ease of application implies however that an understanding of the various techniques, often also at an intuitive level, is imperative. For both students and first time users or even practitioners with some experience, it is important to be able to choose an appropriate processing technique, and furthermore be aware of the errors involved as well as their control. These aspects are usually more difficult to master than the straightforward task of applying specific signal processing methods. It is specifically towards these objectives that the present text is oriented. As an example we may consider the topic of digital filters. This text is based on the assumption that existing software packages minimize the effort involved in designing such filters. It is however the problem of choosing the necessary filter types, their parameters, and the effect of that choice on the filtering results that is often more difficult to address. For example, the topic of actually designing filters, extensively covered in many texts on signal processing, is kept to an absolute minimum. Here, it is the use of the filters that is deemed to be of interest. Another example would be spectral analysis, where the aspects of engineering units and control of errors are emphasized.