signalprocesser

A signal processor is a device or software that performs mathematical operations on signals to modify, analyze, or extract information from them. The term covers both digital signal processing (DSP), which works on discrete-time signals using software or dedicated hardware, and analog signal processing (ASP), which manipulates continuous-time signals with analog circuits. Digital signal processors are optimized for real-time arithmetic, often featuring specialized instruction sets and hardware accelerators, while analog approaches rely on components such as filters, amplifiers, and mixers.

Historically, signal processing concepts emerged in the mid-20th century with developments in filtering and spectral analysis. The rise of fast algorithms and affordable microprocessors led to software-based DSP, followed by the growth of dedicated DSP chips, application-specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs). More recently, processing is increasingly integrated into general-purpose processors and system-on-chip designs, sometimes combining software and hardware acceleration for efficiency.

A typical signal processing system includes input and output interfaces, memory, and a processing core. Processing units perform operations such as convolution, filtering (finite impulse response and infinite impulse response), and transforms (notably the fast Fourier transform), as well as modulation, encoding, decimation, and spectral analysis. Algorithms may be implemented in software on a CPU, in dedicated DSP hardware, or in reconfigurable logic.

Applications span communications, audio and speech processing, image and video processing, radar and sonar, biomedical signal analysis, and consumer electronics. Performance is measured by metrics such as sample rate, word length, latency, throughput, and power efficiency. Ongoing trends include machine learning integration, adaptive and real-time processing, and edge computing on mobile and embedded platforms.