Digital Signal Processing

2009 ◽  
pp. 53-68
Author(s):  
Terrence D. Lagerlund
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Frequency Domain ◽  
Time Domain ◽  
Clinical Neurophysiology ◽  
Digital Signal ◽  
Digital Filtering ◽  
Digital Processing ◽  
Domain Analysis ◽  
Frequency Domain Analysis

This chapter reviews the principles of digitization, the design of digitally based instruments for clinical neurophysiology, and several common uses of digital processing, including averaging, digital filtering, and some types of time-domain and frequency-domain analysis. An understanding of these principles is necessary to select and use digitally based instruments appropriately and to understand their unique features.

Digital Signal Processing

2016 ◽  
pp. 222-235 ◽  
Author(s):  
Terrence D. Lagerlund
Keyword(s):  
Signal Processing ◽  
Time Domain ◽  
Visual Analysis ◽  
Clinical Neurophysiology ◽  
Digital Signal ◽  
Digital Processing ◽  
Frequency Domain Analysis ◽  
Scientific Investigations ◽  
Key Features ◽  
Digital Computers

Digital computers can perform types of signal processing not readily available with analog devices, such as ordinary electrical circuits. This includes making the process of obtaining, storing, retrieving, and viewing clinical neurophysiology data easier; aiding in extracting information from waveforms that is not readily obtainable with visual analysis alone; and improving quantification of key features of waveforms. These processes are useful in accurate clinical diagnosis of electroencephalographic (EEG), electromyographic (EMG), and evoked potential studies, and it also lend themselves to serial comparisons between studies performed on the same subject at different times or between two groups of subjects in scientific investigations. Digital computers may also partially automate the interpretation of clinical neurophysiology studies. This chapter reviews the principles of digitization, the design of digitally based instruments for clinical neurophysiology, and several common uses of digital processing, including averaging, digital filtering, and some types of time-domain and frequency-domain analysis.

scholarly journals Analysis of Three-Phase Wye-Delta Connected LLC

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3606
Author(s):  
Jing-Yuan Lin ◽  
Chuan-Ting Chen ◽  
Kuan-Hung Chen ◽  
Yi-Feng Lin
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Operation Time ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Complete Analysis ◽  
Plane Analysis ◽  
Analysis Methods ◽  
Three Phase

Three-phase wye–delta LLC topology is suitable for voltage step down and high output current, and has been used in the industry for some time, e.g., for server power and EV charger. However, no comprehensive circuit analysis has been performed for three-phase wye–delta LLC. This paper provides complete analysis methods for three-phase wye–delta LLC. The analysis methods include circuit operation, time domain analysis, frequency domain analysis, and state–plane analysis. Circuit operation helps determine the circuit composition and operation sequence. Time domain analysis helps understand the detail operation, equivalent circuit model, and circuit equation. Frequency domain analysis helps obtain the curve of the transfer function and assists in circuit design. State–plane analysis is used for optimal trajectory control (OTC). These analyses not only can calculate the voltage/current stress, but can also help design three-phase wye-delta connected LLC and provide the OTC control reference. In addition, this paper uses PSIM simulation to verify the correctness of analysis. At the end, a 5-kW three-phase wye–delta LLC prototype is realized. The specification of the prototype is a DC input voltage of 380 V and output voltage/current of 48 V/105 A. The peak efficiency is 96.57%.

Study on Auto-Search Algorithm Based on Subsection Correlation for Loran-C

2012 ◽  
Vol 241-244 ◽  
pp. 1751-1755
Author(s):  
Yin Bing Zhu ◽  
Ke Jing Cao ◽  
Bao Li
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Arrival Time ◽  
Search Algorithm ◽  
Digital Signal ◽  
Digital Processing ◽  
Digital Receiver ◽  
Maximum Correlation ◽  
Key Steps ◽  
Signal Search

Auto-search is one of the key steps in digital signal processing for Loran-C receivers, however, for digital sampling Loran-C signal, the principle search algorithm is unable to realize signal search veraciously because of the asynchronism between sampling clock and transmitting station clock. For this question, an auto-search algorithm based on subsection correlation for Loran-C is presented after analyzing the principle search algorithm. The experiment results show that for the received digital Loran-C signal, there are several correlation and accumulation values of master and secondary stations to exceed the search thresholds; the maximum correlation and accumulation value of the presented algorithm is far higher than that of the principle algorithm. That is to say, the presented algorithm can search the arrival time of master and secondary station successfully, solve the problem of clock asynchronism effectively, and enhance the search sensitivity of the receiver, which have great significance for digital processing of Loran-C signal and the engineering realization of Loran-C digital receiver.

scholarly journals A Method of Increasing Digital Filter Performance Based on Truncated Multiply-Accumulate Units

2020 ◽  
Vol 10 (24) ◽  
pp. 9052
Author(s):  
Pavel Lyakhov ◽  
Maria Valueva ◽  
Georgii Valuev ◽  
Nikolai Nagornov
Keyword(s):  
Signal Processing ◽  
Theoretical Analysis ◽  
Digital Signal Processing ◽  
Digital Filter ◽  
Digital Filters ◽  
Digital Signal ◽  
Digital Filtering ◽  
Filter Performance ◽  
Filter Architecture ◽  
Hardware Costs

This paper proposes new digital filter architecture based on a modified multiply-accumulate (MAC) unit architecture called truncated MAC (TMAC), with the aim of increasing the performance of digital filtering. This paper provides a theoretical analysis of the proposed TMAC units and their hardware simulation. Theoretical analysis demonstrated that replacing conventional MAC units with modified TMAC units, as the basis for the implementation of digital filters, can theoretically reduce the filtering time by 29.86%. Hardware simulation showed that TMAC units increased the performance of digital filters by up to 10.89% compared to digital filters using conventional MAC units, but were associated with increased hardware costs. The results of this research can be used in the theory of digital signal processing to solve practical problems such as noise reduction, amplification and suppression of the frequency spectrum, interpolation, decimation, equalization and many others.

A Frequency Domain Analysis of Learning Control

1994 ◽  
Vol 116 (4) ◽  
pp. 781-786 ◽  
Author(s):  
C. J. Goh
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Linear Time ◽  
Planning Horizon ◽  
Time Domain Analysis ◽  
Learning Control ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Convergence Criterion ◽  
The Time Domain

The convergence of learning control is traditionally analyzed in the time domain. This is because a finite planning horizon is often assumed and the analysis in time domain can be extended to time-varying and nonlinear systems. For linear time-invariant (LTI) systems with infinite planning horizon, however, we show that simple frequency domain techniques can be used to quickly derive several interesting results not amenable to time-domain analysis, such as predicting the rate of convergence or the design of optimum learning control law. We explain a paradox arising from applying the finite time convergence criterion to the infinite time learning control problem, and propose the use of current error feedback for controlling possibly unstable systems.

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