Skip to main content

Pole-Zero Frequency Manipulation (with Example)


Pole-Zero Frequency Manipulation: 40 Hz, 50 Hz, 60 Hz

This example demonstrates how to cancel, amplify, and attenuate specific frequencies using pole-zero placement in analog and digital filters. We target sinusoids at 40 Hz, 50 Hz, and 60 Hz.

1. Analog Example (s-domain)

We have a signal:

x(t) = sin(2Ï€·40 t) + sin(2Ï€·50 t) + sin(2Ï€·60 t)

Step 1: Convert frequencies to angular frequency

  • 40 Hz → ω₁ = 2Ï€·40 ≈ 251.33 rad/s
  • 50 Hz → ω₂ = 2Ï€·50 ≈ 314.16 rad/s
  • 60 Hz → ω₃ = 2Ï€·60 ≈ 376.99 rad/s

Step 2: Construct filters

Notch filter at 50 Hz (cancel 50 Hz):

Hnotch(s) = (s² + ω₂²) / (s² + 2ζω₂s + ω₂²)

Zero at ±Ï‰₂ cancels 50 Hz; poles define notch width via damping ζ.

Resonator at 40 Hz (amplify 40 Hz):

Hres(s) = 1 / (s² + 2ζ₁ω₁ s + ω₁²)

Poles near ±Ï‰₁ amplify 40 Hz; damping ζ₁ controls resonance sharpness.

Low-pass effect for 60 Hz (attenuate 60 Hz):

HLP(s) = ωc / (s + ωc), ωc << ω₃

Step 3: Combine filters

H(s) = Hnotch(s) · Hres(s) · HLP(s)

Result: 50 Hz is cancelled, 40 Hz is amplified, 60 Hz is attenuated.

2. Digital Example (z-domain)

Sampling frequency: fs = 500 Hz

Step 1: Normalize frequencies (0–Ï€ rad/sample)

  • 40 Hz → ω₁ = 2Ï€·40 / 500 ≈ 0.502 rad/sample
  • 50 Hz → ω₂ ≈ 0.628 rad/sample
  • 60 Hz → ω₃ ≈ 0.754 rad/sample

Step 2: Notch filter at 50 Hz

Hnotch(z) = (1 - 2 cos(ω₂) z⁻¹ + z⁻²) / (1 - 2 r cos(ω₂) z⁻¹ + r² z⁻²), r ≈ 0.95

Zero at z = e^{±jω₂} cancels 50 Hz; r controls notch width.

Step 3: Resonator at 40 Hz (all-pole)

Hres(z) = 1 / (1 - 2 r₁ cos(ω₁) z⁻¹ + r₁² z⁻²), r₁ ≈ 0.99

Sharp resonance at 40 Hz; amplifies amplitude.

Step 4: Low-pass effect for 60 Hz

HLP(z) = 1 - α z⁻¹, 0 < α < 1

Attenuates high-frequency 60 Hz component.

Step 5: Combine filters

H(z) = Hnotch(z) · Hres(z) · HLP(z)

Result: Frequency response shows 50 Hz cancelled, 40 Hz amplified, 60 Hz degraded.

3. Teaching Insights

  • Zero placement → cancels specific frequencies (notch filter)
  • Pole placement → amplifies frequencies (resonator)
  • Damping or r values → control bandwidth of effect
  • Combined effect → shapes amplitude of multiple sinusoids in a signal
  • Exact cancellation requires precise matching of pole and zero locations

4. Optional Visualization Tips

  • Plot magnitude response |H(jω)| for analog filter
  • Plot |H(e^{jω})| for digital filter
  • Show time-domain input and output signals to illustrate amplification, cancellation, and attenuation

Contact Us

Name

Email *

Message *

Popular Posts

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...(MATLAB Code + Simulator)

Bit Error Rate (BER) & SNR Guide Analyze communication system performance with our interactive simulators and MATLAB tools. 📘 Theory 🧮 Simulators 💻 MATLAB Code 📚 Resources BER Definition SNR Formula BER Calculator MATLAB Comparison 📂 Explore M-ary QAM, PSK, and QPSK Topics ▼ 🧮 Constellation Simulator: M-ary QAM 🧮 Constellation Simulator: M-ary PSK 🧮 BER calculation for ASK, FSK, and PSK 🧮 Approaches to BER vs SNR What is Bit Error Rate (BER)? The BER indicates how many corrupted bits are received compared to the total number of bits sent. It is the primary figure of merit f...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Home / Engineering & Other Exams / UGC NET 2022 PYQ ⬇️ Download Papers and Solutions 📋 Exam Pattern 💡 Preparation Tips ❓ FAQs 📥 Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading UGC-NET (Electronics Science, Subject code: 88) Subject_Code : 88; Department : Electronic Science; 📂 View All Question Papers Q. UGC Net Electronic Science Question Paper [June 2025] A. UGC Net Electronic Science Question Paper With Answer Key Download Pdf [June 2025] with full explanation Q. UGC Net Electronic Science Question Paper [December 2024] A. UGC Net Electronic Science Question Paper With Answer Key Download Pdf [December 2024] ...

Constellation Diagrams of ASK, PSK, and FSK (with MATLAB Code + Simulator)

Constellation Diagrams: ASK, FSK, and PSK Comprehensive guide to signal space representation, including interactive simulators and MATLAB implementations. 📘 Overview 🧮 Simulator ⚖️ Theory Q-function 📚 Resources 📂 Other Topics: M-ary PSK & QAM Diagrams ▼ 🧮 Simulator for M-ary PSK Constellation 🧮 Simulator for M-ary QAM Constellation BASK (Binary ASK) Modulation Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1. BFSK (Binary FSK) Modulation Transmits one of two signals: +√Eb​ (On the y-axis, the phas...

MATLAB Code for ASK, FSK, and PSK (with Online Simulator)

MATLAB Code for ASK, FSK, and PSK Comprehensive implementation of digital modulation and demodulation techniques with simulation results. 📘 Theory 📡 ASK Code 📶 FSK Code 🎚️ PSK Code 🕹️ Simulator 📚 Further Reading Amplitude Shift Frequency Shift Phase Shift Live Simulator ASK, FSK & PSK HomePage MATLAB Code MATLAB Code for ASK Modulation and Demodulation COPY % The code is written by SalimWireless.Com clc; clear all; close all; % Parameters Tb = 1; fc = 10; N_bits = 10; Fs = 100 * fc; Ts = 1/Fs; samples_per_bit = Fs * Tb; rng(10); binar...

Online Simulator for ASK, FSK, and PSK

Interactive Digital Signal Processing (DSP) Tutorial and Simulator for ASK, FSK, and BPSK modulation techniques. Try our new Digital Signal Processing Simulator!   •   Interactive ASK, FSK, and BPSK tools updated for 2025. Start Now Digital Modulation Visualizer: ASK, FSK, & BPSK Simulator Learn and visualize binary modulation techniques (ASK, FSK, BPSK) in real-time with adjustable carrier and sampling parameters. Perfect for DSP students and engineers. 📡 ASK Simulator 📶 FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator More Topics 1. ASK (Amplitude Shift Keying) Simulat...

MATLAB code for BER vs SNR for M-QAM, M-PSK, QPSk, BPSK, ...(with Online Simulator)

🧮 MATLAB Code for BPSK, M-ary PSK, and M-ary QAM Together 🧮 MATLAB Code for M-ary QAM 🧮 MATLAB Code for M-ary PSK 📚 Further Reading MATLAB Script for BER vs. SNR for M-QAM, M-PSK, QPSK, BPSK % Written by Salim Wireless clc; clear; close all; snr_db = -5:2:25; psk_orders = [2, 4, 8, 16, 32]; qam_orders = [4, 16, 64, 256]; ber_psk_results = zeros(length(psk_orders), length(snr_db)); ber_qam_results = zeros(length(qam_orders), length(snr_db)); for i = 1:length(psk_orders) ber_psk_results(i, :) = berawgn(snr_db, 'psk', psk_orders(i), 'nondiff'); end for i = 1:length(qam_orders) ber_qam_results(i, :) = berawgn(snr_db, 'qam', qam_orders(i)); end figure; semilogy(snr_db, ber_psk_results(1, :), 'o-', 'LineWidth', 1.5, 'DisplayName', 'BPSK'); hold on; for i = 2:length(psk_orders) semilogy(snr_db, ber_psk_results(i, :), 'o-', 'DisplayName', sprintf('%d-PSK', psk_or...

BER performance of QPSK with BPSK, 4-QAM, 16-QAM, 64-QAM, 256-QAM, etc (MATLAB + Simulator)

📘 Overview 📚 QPSK vs BPSK and QAM: A Comparison of Modulation Schemes in Wireless Communication 📚 Real-World Example 🧮 MATLAB Code 📚 Further Reading   QPSK provides twice the data rate compared to BPSK. However, the bit error rate (BER) is approximately the same as BPSK at low SNR values when gray coding is used. On the other hand, QPSK exhibits similar spectral efficiency to 4-QAM and 16-QAM under low SNR conditions. In very noisy channels, QPSK can sometimes achieve better spectral efficiency than 4-QAM or 16-QAM. In practical wireless communication scenarios, QPSK is commonly used along with QAM techniques, especially where adaptive modulation is applied. Modulation Bits/Symbol Points in Constellation Usage Notes BPSK 1 2 Very robust, used in weak signals QPSK 2 4 Balanced speed & reliability 4-QAM ...

Q-function in BER vs SNR Calculation

Q-function in BER vs. SNR Calculation In the context of Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) calculations, the Q-function plays a significant role, especially in digital communications and signal processing . What is the Q-function? The Q-function is a mathematical function that represents the tail probability of the standard normal (Gaussian) distribution. Specifically, it is defined as: Q(x) = (1 / sqrt(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt In simpler terms, the Q-function gives the probability that a standard normal random variable exceeds a value x . It is the complementary cumulative distribution function (CCDF) of the standard Gaussian distribution. The Role of the Q-function in BER vs. SNR The Q-function is the standard tool for calculating the Bit Error Rate (BER) in digital communication systems like Binary Phase Shift Keying (BPSK) or Quadrature Phase Shift Keying (QPSK) , where noise follows a Gaussian dis...