in [Digital Signal Processing](https://www.ampheo.com/c/dsp-digital-signal-processors) ([DSP](https://www.ampheo.com/c/dsp-digital-signal-processors)), signals are classified in several ways depending on their properties. Here’s a structured breakdown:

**Types of Signals in DSP**
**1. Based on Continuity**

**Continuous-Time Signal**

* Defined for every instant of time 𝑥(𝑡).
* Example: audio waveform in analog form.

**Discrete-Time Signal**

* Defined only at discrete instants (sampled values) 𝑥[𝑛].
* Example: sampled audio in a digital system.

**2. Based on Value Range**

**Analog Signal**

Amplitude can take infinite values (continuous range).

**Digital Signal**

Amplitude takes only finite values (quantized levels after [ADC](https://www.onzuu.com/category/analog-to-digital-converters)).

In DSP, we mostly handle discrete-time, digital signals (sampled & quantized).

**3. Based on Symmetry**

* Even Signal: x[n]=x[−n] (symmetric about the vertical axis).
* Odd Signal: x[n]=−x[−n] (anti-symmetric).

**4. Based on Energy and Power**

* Energy Signal: Finite energy, zero average power.

Example: finite-duration pulses.

* Power Signal: Finite power, infinite energy.

Example: sinusoidal signals, periodic waveforms.

**5. Based on Determinism**

**Deterministic Signal**

* Exactly predictable at any time.
* Example: pure sine wave.

**Random (Stochastic) Signal**

* Cannot be predicted exactly, described statistically.
* Example: noise.

**6. Based on Periodicity**

**Periodic Signal**

* Repeats after a fixed interval 𝑁: x[n]=x[n+N].
* Example: sine, cosine, square wave.

**Aperiodic Signal**

* Does not repeat.
* Example: speech, transient signals.

**7. Based on Causality**

**Causal Signal**

* Nonzero only for n≥0.

**Non-Causal Signal**

* Nonzero for n<0.

**Anti-Causal Signal**

* Nonzero only for n<0.

**8. Special Signals in DSP**

* Unit Impulse δ[n] → basic building block for LTI analysis.
* Unit Step u[n] → used in system response analysis.
* Ramp → increasing sequence.
* Exponential → growth/decay signals.
* Sinusoids → fundamental in Fourier analysis.

**Summary**

In [DSP](https://www.ampheoelec.de/c/dsp-digital-signal-processors), signals are classified by time domain (continuous/discrete), value domain (analog/digital), symmetry (even/odd), energy/power, predictability (deterministic/random), periodicity, and causality. Additionally, standard signals like impulse, step, and sinusoids are used as mathematical tools for system analysis.