Skip to main content

A Brief Discussion of Filters

 

Low Pass Filter

In most cases, filters extract the required frequency from a signal. Low-pass filters only permit frequencies falling below and attenuating frequencies above the cutoff frequency.

Low-pass filters generally have a form where the output decays at higher frequencies.

Low-Pass Filter Transfer Function

Let’s take the following simple transfer function:

\[ H(z) = \frac{1}{1 + 0.5z^{-1}} \]

Analysis of the Transfer Function

The denominator suggests it’s a low-pass filter because it has a single pole and the gain decreases as frequency increases (in the discrete-time case, this is for higher \(\omega\)).

At low frequencies, the magnitude will be close to 1, but as the frequency increases, the magnitude will drop.

Fig: Low Pass Filter

A low pass filter's cutoff frequency is calculated as

Cut off frequency = 1 / 2*pi*R*C


High Pass Filter

All frequencies in a signal above the high pass filter's cutoff frequency can pass through the high pass filter. High-pass filters generally have a form where the output increases at higher frequencies.

High-Pass Filter Transfer Function

Now consider the following transfer function:

\[ H(z) = \frac{z^{-1}}{1 + 0.5z^{-1}} \]

Analysis of the Transfer Function

The numerator has z^{-1}, suggesting a high-pass filter because it includes a term that shifts the response at low frequencies, while passing higher frequencies more easily.

By examining the transfer function, you can classify the filter's behavior in terms of its frequency response.

Fig: High Pass Filter

A high pass filter's cutoff frequency is calculated as

Cut off frequency = 1 / 2*pi*R1*C1


Band Pass Filter

A band pass filter is a device that permits frequencies that fall within a specific frequency range. Both frequencies inside and outside of the field are attenuated. Band-pass filters will show a peak or resonance at a specific frequency.

Bandpass Filter Transfer Function

Now consider the following transfer function for a bandpass filter:

\[ H(z) = \frac{z^{-1} - z^{-2}}{1 + 0.5z^{-1} + 0.25z^{-2}} \]

Analysis of the Transfer Function

The numerator contains the terms z^{-1} and z^{-2}, suggesting that the filter allows a band of frequencies to pass while attenuating lower and higher frequencies.

The filter achieves this by having a zero at a specific frequency, which creates a notch at the desired frequency, thus passing a band of frequencies in the middle.

By examining the transfer function, you can classify the filter's behavior in terms of its frequency response. This includes its ability to pass signals within a specific frequency band and attenuate others outside that range.

Fig: Band Pass Filter
All frequencies above (1/2*pi*R1*C1) and below (1/2*pi*R2*C2) are passed by the band pass filter shown in the figure above.

Keep in mind that a bandpass filter is a combination of a high pass and a low pass filter.


Further Reading


People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

Channel Impulse Response (CIR)

📘 Overview & Theory 📘 How CIR Affects the Signal 🧮 Online Channel Impulse Response Simulator 🧮 MATLAB Codes 📚 Further Reading What is the Channel Impulse Response (CIR)? The Channel Impulse Response (CIR) is a concept primarily used in the field of telecommunications and signal processing. It provides information about how a communication channel responds to an impulse signal. It describes the behavior of a communication channel in response to an impulse signal. In signal processing, an impulse signal has zero amplitude at all other times and amplitude ∞ at time 0 for the signal. Using a Dirac Delta function, we can approximate this. Fig: Dirac Delta Function The result of this calculation is that all frequencies are responded to equally by δ(t) . This is crucial since we never know which frequenci...

Gaussian minimum shift keying (GMSK)

📘 Overview & Theory 🧮 Simulator for GMSK 🧮 MSK and GMSK: Understanding the Relationship 🧮 MATLAB Code for GMSK 📚 Simulation Results for GMSK 📚 Q & A and Summary 📚 Further Reading Dive into the fascinating world of GMSK modulation, where continuous phase modulation and spectral efficiency come together for robust communication systems! Core Process of GMSK Modulation Phase Accumulation (Integration of Filtered Signal) After applying Gaussian filtering to the Non-Return-to-Zero (NRZ) signal, we integrate the smoothed NRZ signal over time to produce a continuous phase signal: θ(t) = ∫ 0 t m filtered (Ī„) dĪ„ This integration is crucial for avoiding abrupt phase transitions, ensuring smooth and continuous phase changes. Phase Modulation The next step involves using the phase signal to modulate a...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...

Wireless Communication Interview Questions | Page 2

Wireless Communication Interview Questions Page 1 | Page 2| Page 3| Page 4| Page 5   Digital Communication (Modulation Techniques, etc.) Importance of digital communication in competitive exams and core industries Q. What is coherence bandwidth? A. See the answer Q. What is flat fading and slow fading? A. See the answer . Q. What is a constellation diagram? Q. One application of QAM A. 802.11 (Wi-Fi) Q. Can you draw a constellation diagram of 4QPSK, BPSK, 16 QAM, etc. A.  Click here Q. Which modulation technique will you choose when the channel is extremely noisy, BPSK or 16 QAM? A. BPSK. PSK is less sensitive to noise as compared to Amplitude Modulation. We know QAM is a combination of Amplitude Modulation and PSK. Go through the chapter on  "Modulation Techniques" . Q.  Real-life application of QPSK modulation and demodulation Q. What is  OFDM?  Why do we use it? Q. What is the Cyclic prefix in OFDM?   Q. In a c...

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 distribution. Specifically, it is defined as: Q(x) = (1 / sqrt(2Ī€)) ∫ₓ∞ e^(-t² / 2) dt In simpler terms, the Q-function gives the probability that a standard normal random variable exceeds a value x . This is closely related to the complementary cumulative distribution function of the normal distribution. The Role of the Q-function in BER vs. SNR The Q-function is widely used in the calculation of the Bit Error Rate (BER) in communication systems, particularly in systems like Binary Phase Shift Ke...

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM 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 phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...

MATLAB code for Pulse Code Modulation (PCM) and Demodulation

📘 Overview & Theory 🧮 Quantization in Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Amplitude Modulation and Demodulation of Digital data 🧮 Other Pulse Modulation Techniques (e.g., PWM, PPM, DM, and PCM) 📚 Further Reading MATLAB Code for Pulse Code Modulation clc; close all; clear all; fm=input('Enter the message frequency (in Hz): '); fs=input('Enter the sampling frequency (in Hz): '); L=input('Enter the number of the quantization levels: '); n = log2(L); t=0:1/fs:1; % fs nuber of samples have tobe selected s=8*sin(2*pi*fm*t); subplot(3,1,1); t=0:1/(length(s)-1):1; plot(t,s); title('Analog Signal'); ylabel('Amplitude--->'); xlabel('Time--->'); subplot(3,1,2); stem(t,s);grid on; title('Sampled Sinal'); ylabel('Amplitude--->'); xlabel('Time--->'); % Quantization Process vmax=8; vmin=-vmax; %to quanti...