Signal processing is a field of engineering, mathematics, and computer science that deals with processing, analyzing, and manipulating analog and digital signals. Signals can be audio, video, sensor data, images, and many other types of data. Signal processing techniques are used in a wide range of applications, including telecommunications, audio and video processing, image processing, speech recognition, and control systems. Some common signal-processing tasks include filtering, noise reduction, compression, and feature extraction.

Digital Signal Processing
Digital signal processing (DSP) is a subfield of signal processing that deals specifically with the representation and manipulation of signals in a discrete format. This means that in digital signal processing, the input signals must first be or converted into a digital format (discrete format), which can then be manipulated using digital mathematical operations. 

Applications
Signal processing techniques are used in a wide range of applications, including:

1. Telecommunications: Signal processing techniques are used in telecommunications to transmit, receive, and process signals over communication channels. This includes tasks such as modulation, demodulation, error correction, and signal amplification.
2. Audio and video processing: Signal processing techniques are used to enhance the quality and clarity of audio and video signals, as well as to extract features such as speech, music, and moving objects.
3. Image processing: Signal processing techniques are used to improve the quality and resolution of images, as well as to extract features such as edges, shapes, and textures.
4. Speech recognition: Signal processing techniques are used to analyze and interpret speech signals, enabling the development of systems that can transcribe speech or recognize spoken commands.
5. Control systems: Signal processing techniques are used in control systems to stabilize and optimize the performance of systems by processing feedback signals from sensors and actuators.
6. Biomedical engineering: Signal processing techniques are used in biomedical engineering to analyze and interpret signals from medical devices such as electrocardiograms (ECGs) and magnetic resonance imaging (MRI) scanners.
7. Financial engineering: Signal processing techniques are used in financial engineering to analyze and interpret financial data and to develop predictive models for financial markets.

How Signal Processing Works?
Signal processing involves the representation, manipulation, and analysis of analog and digital signals. The steps involved can vary depending on the specific application and the goals of the signal processing system.

The outline of signal processing

Here are the general outline of signal processing:
1. Signal acquisition: The first step in signal processing is to acquire the input signal. This may involve using sensors to measure physical quantities such as temperature, pressure, or acceleration, or it may involve capturing audio, video, or other types of data.
2. Signal conversion: If the input signal is in an analog format, it may need to be converted into a digital format using an analog-to-digital converter (ADC). This allows the signal to be processed using digital techniques, such as mathematical operations and algorithms.
3. Signal representation: The input signal is then represented in a suitable form for processing. This may involve representing the signal as a discrete sequence of samples or as a continuous function.
4. Signal manipulation: The input signal is then manipulated using various techniques such as filtering, noise reduction, compression, and feature extraction. These techniques can be implemented using algorithms and mathematical operations.
5. Signal analysis: The manipulated signal is then analyzed to extract useful information or to make decisions. This may involve detecting patterns or features in the signal, classifying the signal into different categories, or estimating the values of certain parameters.
6. Signal synthesis: The output of the signal processing system may be a synthesized signal, which is generated based on the processed input signal and any additional information or constraints.
7. Signal output: The final step in signal processing is to output the resulting signal. This may involve converting the signal back to an analog format using a digital-to-analog converter (DAC) or displaying the signal on a screen or speaker.