Introduction to FIR Filters

Definition

• FIR Filter: Stands for Finite Impulse Response filter.
  • Has a finite number of samples in its impulse response.
  • Output depends on present and past input values.

Key Characteristics

• Impulse Response: Finite length, distinguishing it from infinite impulse response filters.
• Stability: Non-recursive FIR filters are always stable; values do not repeat.
• Phase Distortion: FIR filters can eliminate undesirable phase distortion caused by non-linear characteristics of frequency response.
• Recursive FIR Filters: Can be implemented, where current output depends on previous output.
• Transient Effects: Startup transients have a small duration.
• Quantization Noise: Non-recursive FIR filters can make quantization noise negligible.

Applications

• Linear Phase Preservation: Important in communication and medical imaging to maintain the shape of the input signal.
• Major Uses:
  • Data transmission
  • Speech processing
  • Correlation processing
  • Interpolation

Advantages of FIR Filters

• Stability: Non-recursive nature ensures stability.
• Structure: Can be realized in both recursive and non-recursive forms.
• Linear Phase: Can achieve exact linear phase.
• Flexibility: Highly flexible design procedures for any magnitude response.
• Low Sensitivity: Less sensitive to quantization noise.
• Efficient Hardware Realization: Can be efficiently implemented in hardware.

Disadvantages of FIR Filters

• Complexity: Practical realization can be complex.
• Storage Requirement: Requires more filter coefficients compared to IIR filters.
• Processing Needs: Long duration impulse responses require significant processing power.
• Cost: More costly due to narrow transition bands needing more arithmetic operations and hardware components.

Conclusion

• FIR filters have distinct advantages in signal processing, particularly in maintaining linear phase and stability but come with complexity and cost considerations.