🎛️ DSP Architecture & Filter Visualizer

🎯 Getting Started

This tool demonstrates DSP architecture and digital filtering concepts used in modern communication systems.

• DSP Architecture: View the block diagram showing core DSP components
• Filter Type: Choose between FIR (Finite Impulse Response) or IIR (Infinite Impulse Response)
• Adjust Coefficients: Use sliders to modify filter tap weights and see real-time effects
• Signal Visualization: See how the filter removes noise from a noisy input signal
• Frequency Response: View the filter's magnitude and phase response

🔬 DSP Architecture Components

• ADC (Analog-to-Digital Converter): Converts analog signals to digital samples
• DSP Core: Performs mathematical operations on digital samples (filtering, FFT, etc.)
• Memory (RAM/ROM): Stores filter coefficients, signal buffers, and program code
• MAC Unit: Multiply-Accumulate unit for efficient filter operations
• DAC (Digital-to-Analog Converter): Converts processed digital data back to analog

📡 Filter Types

• FIR (Finite Impulse Response):
  • Uses only current and past input samples
  • Always stable, linear phase possible
  • Equation: y[n] = b₀x[n] + b₁x[n-1] + b₂x[n-2] + ...
• IIR (Infinite Impulse Response):
  • Uses past output samples (feedback) in addition to input samples
  • More efficient (fewer taps needed), but can be unstable
  • Equation: y[n] = b₀x[n] + b₁x[n-1] - a₁y[n-1] - a₂y[n-2]

💡 Key Concepts

• Filter Coefficients: Weights applied to each sample in the filter calculation
• Cutoff Frequency: Frequency where the filter begins attenuating signals
• Noise Removal: Filters remove unwanted high-frequency noise while preserving the signal
• Real-time Processing: DSPs can process signals as they arrive (streaming)