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




Contact Us

Name

Email *

Message *

Popular Posts

LDPC Encoding and Decoding Techniques

Low Density Parity Check (LDPC) Guide Comprehensive analysis of linear error-correcting block codes, Tanner graphs, and 5G-NR implementations. 📘 Overview 🧮 Encoding 🧩 Decoding 📚 Resources Theory Encoding Tech Tanner Graph 5G Encoding Decoding 'LDPC' is the abbreviation for 'low density parity check'. LDPC code H matrix contains very few amount of 1's and mostly zeroes. LDPC codes are error correcting code. Using LDPC codes, channel capacities that are close to the theoretical Shannon limit can be achieved. Low density parity check (LDPC) codes are linear error-correcting block code suitable for error correction in a large block sizes transmi...

Flat vs Frequency Selective Online Simulator

Flat vs Frequency Selective Online Simulator Channel Type Without Fading Flat Fading Multipaths Nakagami m SNR(dB) Run Simulation Input Signal Signal After Fading Constellation Diagram BER vs SNR Explore Advanced Flat vs Frequency-Selective Fading Simulator Want to see these equations in action? Visualize it. Launch Simulator Tool Return to DSP Simulations Main Page →

Online Simulator for ASK, FSK, and PSK Signal Generation

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 đŸ“ļ FSK Simulator 🎚️ BPSK Simulator 📚 More Topics ASK Modulator FSK Modulator BPSK Modulator Demodulation More Topics 1. ASK (Ampli...

Design of CMOS Flip-Flops (SR, D, JK)

Design of CMOS Flip-Flops (SR, D, JK) A flip-flop or latch is a circuit with two stable states, used to store state information. It is the basic storage element in sequential logic and a fundamental building block in digital electronics systems, including computers and communication devices. Flip-flops and latches act as data storage elements for states, pulse counting, and synchronization of variably-timed input signals to a reference clock. Flip-flops can be transparent/opaque (latches) or clocked (synchronous, edge-triggered). Latches are level-sensitive, while flip-flops are edge-sensitive. In sequential logic, the output depends on current inputs and previous states. Fig.1 shows a sequential circuit combining a combinational block and a memory element. ...

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 signal to produce a continuous phase signal. For GMSK, the modulation index is $h=0.5$, meaning a bit '1' results in a phase shift of $\pi/2$: θ(t) = 2Ī€h ∫ 0 t m filtered (Ī„) dĪ„ This integration is crucial for avoiding abrupt phase transitions, ensuring smooth and continuous phase changes. Phase Mo...

UGC NET Electronic Science Previous Year Question Papers with Solutions

Download Papers and Solutions Exam Pattern Preparation Tips FAQs More Home / Engineering & Other Exams / UGC NET 2026 PYQ 📊 Exam Highlights: Electronic Science (88) Feature Details Junior Research Fellowship (JRF) ₹37,000 + HRA per month Eligibility M.Sc/M.Tech in Electronics (55%) Validity of Certificate JRF (3 Years) | Lectureship (Lifetime) đŸ“Ĩ Download UGC NET Electronics PDFs Complete collection of previous year question papers, answer keys and explanations for Subject Code 88. Start Downloading 📂 View All Question Papers June 2025 - Question Paper Download PDF June 2025 - Sol...

Q-function in BER vs SNR Calculation (with Simulation)

Q-function in BER vs. SNR Calculation In digital communications and signal processing, the Q-function plays a significant role in predicting system reliability. It allows engineers to quantify the probability that Gaussian noise will exceed a specific threshold, causing a bit error. What is the Q-function? The Q-function is a mathematical function representing the tail probability of the standard normal (Gaussian) distribution. It is the complementary cumulative distribution function (CCDF) of a standard Gaussian distribution. Q(x) = (1 / √(2Ī€)) ∫ₓ∞ e^(-t² / 2) dt The Role of the Q-function in BER vs. SNR The Q-function is the standard tool for calculating BER in systems like BPSK or QPSK over AWGN (Additive White Gaussian Noise) channels. For BPSK: In BPSK, we transmit +√E b (bit 1) and -√E b (bit 0). The decision boundary is set at 0 . If -√E b was sent, an error occurs if noise r > √...