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Passive Filters01:27

Passive Filters

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Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
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Active Filters01:25

Active Filters

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Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
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Orthogonal Trajectories01:26

Orthogonal Trajectories

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Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
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Convolution Properties II01:17

Convolution Properties II

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The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
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Convolution Properties I01:20

Convolution Properties I

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Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
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Cognitive Dissonance01:38

Cognitive Dissonance

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Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
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Related Experiment Video

Updated: Feb 9, 2026

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
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Fast Convolution Filter-Bank Based Non-Orthogonal Multiplexed Cognitive Radio (NOMCR) Receiver Design Using

Jayanta Datta1, Hsin-Piao Lin2

  • 1Department of Electrical Engineering and Computer Science, National Taipei University of Technology , Daan District, Taipei City 10608, Taiwan. jdatta1@iit.edu.

Sensors (Basel, Switzerland)
|June 15, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a novel cognitive multicarrier system using Layer Division Multiplexing (LDM) with Fast Convolution Filtered-OFDM (FC-F-OFDM) and Orthogonal Frequency Division Multiplexing (OFDM). The system demonstrates strong bit error rate performance in challenging wireless environments.

Keywords:
ANNNOMCRcyclostationaritymulticarrier

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Area of Science:

  • Wireless communication systems
  • Signal processing
  • Information theory

Background:

  • Non-orthogonal multiple access (NOMA) offers improved spectral efficiency for 5G systems.
  • Layer Division Multiplexing (LDM) is a power-domain NOMA variant often using successive interference cancellation (SIC).
  • Fast convolution based filtered-OFDM (FC-F-OFDM) efficiently processes 5G physical layer signals.

Purpose of the Study:

  • To propose and evaluate a cognitive multicarrier non-orthogonal multiplexed system.
  • To integrate FC-F-OFDM and conventional OFDM as component layers within an LDM framework.
  • To enhance receiver performance using advanced SIC decoding techniques.

Main Methods:

  • A cognitive multicarrier system based on Layer Division Multiplexing (LDM) was designed.
  • The system utilizes FC-F-OFDM and conventional OFDM as its constituent layers.
  • Cyclostationary FREquency SHift (FRESH) filter based SIC decoding with artificial neural network (ANN) processing was implemented.

Main Results:

  • The proposed system demonstrated effective performance in frequency selective Rayleigh fading channels.
  • Good bit error rate (BER) performance was achieved under simulated conditions.
  • The integration of FC-F-OFDM and ANN-based SIC decoding proved beneficial.

Conclusions:

  • The developed cognitive LDM system shows promise for future wireless communication standards.
  • The combination of FC-F-OFDM and FRESH filter based SIC with ANN processing is effective.
  • The system offers a viable approach for enhancing spectral efficiency in 5G networks.