| Feature | FIR Filters | IIR Filters | | :--- | :--- | :--- | | | No feedback (Non-recursive) | Feedback loop (Recursive) | | Stability | Always stable | Can be unstable if poles fall outside the unit circle | | Phase | Can be perfectly linear | Generally non-linear phase | | Order | Higher order required | Lower order for same magnitude response | | Memory | Requires more memory | Requires less memory |
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FIRTGI – F eedback, I ntegration, R esponse time, T racking, G overnance, I mprovement FIRTGI – F eedback, I ntegration, R esponse
Digital signal processing (DSP) relies heavily on filters to manipulate signals for various applications, from telecommunications to medical imaging. Among these, Finite Impulse Response (FIR) filters are a cornerstone due to their inherent stability and linear-phase characteristics. This paper provides an overview of FIR filters, exploring their mathematical foundations, key properties, common design methodologies, and practical applications. A comparison with Infinite Impulse Response (IIR) filters highlights the specific advantages and trade-offs associated with FIR implementations.
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