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Signal Processing Tool Box
1Ameya Bekal, 2Rashmi HN, 3Lawrence Borah
1,2,3Department of Computer Applications, Dayananda Sagar College of Arts Science and Commerce, Bangalore, India
Abstract— Signal processing refers to various techniques for improving the reliability and accuracy of digital communications. The theory behind SP is quite complex.
The main applications [citation needed] of SP are audio signal processing, speech processing audio compression, digital image processing, video compression, speech recognition, digital communications, digital synthesizers, radar, sonar, financial signal processing, seismology and biomedicine. In this research paper we are trying to discuss 2-D and 3-D signals with our Comparative study using math lab tool.
Keywords—
I. INTRODUCTION
Signal processing is a technology that encompasses the fundamental applications, algorithms, theory, and implementations of transferring information contained in many different abstract, physical, symbolic, or formats broadly classified as signals. It uses an Arithmetical, computational, statistical, heuristic, formalisms and linguistic representations, and major techniques for representation, analysis, modeling, synthesis, recovery, sensing, acquisition, discovery, extraction, learning, security, or forensics. Analog signals are those which have not been digitized, as in legacy radio, telephone, radar, and television systems. The former are, for instance, active filters, passive filters, integrators, additive mixers, and delay lines. Non-linear circuits include multiplicators, compandors (voltage-controlled amplifiers and frequency mixers), voltage-controlled filters, voltage-controlled oscillators and phase-locked loops. Continuous-time signal processing is for signals that changes rapidly with domain (without considering some individual interrupted points). The methods of signal processing include frequency domain, time domain, and complex frequency domain. This technology mainly discusses the modeling of linear time-invariant continuous system, integral of the system's zero-state response, setting up system function and the continuous time filtering of deterministic signals. Processing is done by digital circuits such as ASICs, field-programmable gate arrays or specialized digital signal processors (DSP chips). Typical arithmetical operations include floating-point and fixed-
compression, speech processing, speech recognition, digital image processing, digital synthesizers, radar, sonar, financial signal processing, biomedicine and seismology.
II. WHY MATLAB TOOLBOX IS REQUIRED ?
While we are doing the project, basically we thinks about the benefits of project having the most advantages compare to other things. In MatLab we are able to browse the Windows but not in others. And the most important is “database is inbuilt in MatLab”, no need to install other software to get the database. Coding is user friendly in MatLab. No need to insert the query in MatLab. It automatically saves in database when we write the coding. Nobody can delete the database in MatLab. The most considering advantage is the Space Complexity. We need to check the space complexity of our applications. Here MatLab requires very less space compares to other applications. MatLab works with 53KB usually. But DotNet and Other software requires the space in GB. It can affect the storage system of the database. To execute any DotNet queries it is requires the HTML compulsorily. The use of HTML is sometimes in MatLab but not compulsory in all the time.
But other software are must use the HTML like DotNet, Google chrome. But in MatLab there is no require of HTML. MatLab can run on Windows and Mobile with respect to windows size.
III. WHY SIGNAL PROCESSING IS NEEDED
Signal processing (SP) is the manipulation of signals, usually with the intention to filter, measure, produce or compress continuous analog signals. The field of signal processing is a very impressive field of study and one that makes possible various other fields such as Speech recognition systems, communications such as dictation software need to analyze and process signal data to identify individual words in a spoken sentence. The field of signal processing is a very important field of study and one that makes possible various other fields such as communications. Speech recognition systems such as
IV. 2-D SIGNAL REPRESENTATIONS
In this window we are trying to discuss the following:
Bar, Histogram, Plot 1, Plot 2, Stream, Plotty, Polar, Stairs, Semilogx, Area, Rose, Pie etc.
Bar: A diagram in which the numerical values of variables are represented by the height or length of lines or rectangles of equal width.
Figure1: Bar
Hist: Histograms are sometimes confused with bar charts. Ahistogram is used for continuous data, where the bins represent ranges of data.
Figure 2: Histogram
Plot 1: The Plot Diagram is an organizational tool focusing on a pyramid or triangular shape, which is used to map the events in a story.
Figure 3: Plot 1
Plot 2: The Plot Diagram is an organizational tool focusing on a pyramid or triangular shape, which is used to map the events in a story.
Figure 3: Plot 2
Firgure 4: Steam:
Firgure 5: Plotty:
Firgure 6: Polar:
Firgure 7: Stairs
Firgure 8: Semilogx
Firgure 8: Area
Firgure 9: Rose
Firgure 10: Pie
V. 3-D SIGNAL REPRESENTATIONS
Figure 11: 3-D Representation
In this window we are trying to discuss the following:
Globe, Globe_light, Edge color, Surf, Slice, Plot 3,Ezpolar, Sphere, Pie 3, Cylinder etc.
Firgure 13: Globe_Light:
Firgure 14: Edge Color:
Firgure 15: Surf
Firgure 16: Slice
Firgure 18: Ezpolar
Firgure 19: Sphere
Firgure 20: Pie 3
VI. FLOW OF WORK
STEP 1:- This is the first and main form of our project.
The project name is Equation Visualization using MatLab Toolbox. It contains the definition and grip of all other forms. It gives the proper round figure of our whole project. It defines all the forms. After debugging this form we will get the output like this shown below:
STEP 2:- About Project:- This page gives a brief introduction about our research project in which we are trying to represent different types of signals.
MatLab:- After running the first form now, We have to execute the other forms. Now the MatLab Definition will provide you by clicking the MatLab box (push button).
Signal Processing:-The second form of the project is Signal Processing. The Signal Processing definition will provide you by clicking the Signal Processing box (push button).
VII. RESULT AND DISCUSSIOINS
In this research paper we developed one MatLab Equation Visualization tool box for comparison of different existing Signal Processing techniques. Figure 21 shows the Equation visualization tool box window of our research project; Figure 22 shows the 2D Plot window. Figure 23 represents the 3D Plot window.
Figure 24 represents the comparative Comparism between Bar, Hist, Stem, Stairs.
Firgure 21: Tool Box
Firgure 22:2D Plot
Firgure 23:3D Plot
Firgure 24: Comparism between Bar, Hist, Stem, Stairs.
VIII. CONCLUSION
Signal Processing techniques are limited to signals with relatively low bandwidths. The point at which SP becomes too expensive will depend on the application and the current state of conversion and digital processing technology. A human can distinguish differences in shape orientation, Line length and color (hue) readily without significant processing effort; these are referred to as Good Visualization skills. A human can easily learn things by its visuals.
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