Implementing Graphic Equalizer Using Dsk Tms320c6713 Processor Computer Science Essay

In this paper, the Equalizer is implemented as the summation of four band pass filters with different frequencies as a graphic Equalizer. The co-efficient file ‘Equalizer.Cof’ contains the Coefficients of Low-Pass filter (1300Hz), Band-Pass filter1 (1300-2000 Hz), Band-Pass filter2 (2000-2800 Hz), High-Pass filter (2800Hz). The set of coefficients is calculated using MATLAB. The filter is designed with convolution method by transforming both input signal and set of coefficients.

Lab VIEW, is a graphical programming was developed by National Instruments, which is well suited for high-level system design. This paper introduces programming using a Lab VIEW graphs. This paper yields how the Code Composer Studio makes the users to establish communication link between PC of a host who is running Lab VIEW and a C6713 DSK board.

Index Terms- Graphic Equalizer, DSK TMS320C6713 processor, LabVIEW.

I. INTRODUCTION

THE Graphic equalizer makes us to see graphically in an Audio controller and manages different frequency bands individually. Every basic equalizer contains unsimilar sets of same amplifiers for each channel. There are two different types of equalizer techniques.1. Graphic equalization and 2.parametric equalization. We use graphic equalizer called constant Q graphic equalizer. In this paper we explore the DSK kit in which the input and output are supported by TMS320C6713 floating point processor with the Code Composer Studio software. We focus mainly on the design and implementation of equalizer with the digital signal processor. The other portion of this paper draft provides the design techniques, which helps the digital system to execute and run on the processor. The final model of the equalizer in designed using the code composer studio and executed via DSK6713 processor, where in the process , an audio signal is taken as the input function/signal and analyzing the output In order to use the DSP kit we make use of the DSK support tools. The three key components of the DSP kit are Code Composer Studio (CCS), an oscilloscope along with signal generator. CCS provide the supporting tools for the software compatibility like c compiler, Matlab, Simulation

In order to work with DSP we have to first execute some operations with the DSP. That is Quick test. The Quick test is for testing the DSP board for proper functioning..

II. PRE STUDY

A DSP Starter Kit

TMS320C6713 DSP Starter Kit (DSK) gives users a opportune, low cost means of evaluating the features and architecture of theTMS320C6713 Digital Signal Processor from Texas Instruments. Various algorithms are well suited and based on VLIW architecture, on which the TMS320C6713(C6713) is also based on. Both fixed-point processing and floating-point processing can be done by the kit. In order to improve the various applications of signal processing, the stand alone C6713 DSK has introduced a wide range of on board peripherals and interfaces [1].

B FIR Filter Design

The instruction set and architecture of TMS320C6x makes it well appropriate for FIR filtering operations. Digital filter, such as an FIR filter, operates on discrete-time signals and can be implemented with a DSP such as the TMS320C6713 [1]. There are wide methods including a number of tools available to design and implement within a few minutes an FIR filter in real time using the TMS320C6x-based DSK. The filter design

consists of the estimation of a transfer function with a resulting set of coefficients. Different techniques are available

for the design of FIR filters. Fourier series is mostly utilized as computer aided design technique for the designment of FIR filter. The important characteristic feature of FIR filter is that it can guarantee linear phase. The linear phase feature can be very helpful in applications such as speech analysis, where phase distortion can be dangerous. Hence Linear phase filters are FIR filters. However, not all FIR filters have linear phase. Many applications in adaptive filtering and speech processing

such as in a linear predictive coding (LPC) application uses Lattice structure of FIR filters [2]. Approximating the magnitude response of the transfer function to a desired magnitude response is done by making use of Fourier series design method of an FIR filter.

C Graphic Equalizers:

They are very excellent equalizers and are much suited to situations where the actual “modification” is required more.

Achieving the equalization with four different filters which

had fixed frequencies is called the audio graphic equalizer,

which is very efficient. The variation of the magnitude response leads to high quality output sounds. A set of filters together is simply called as Graphic Equalizer, with a fixed center frequency for each filter that cannot be changed.

The only control you have is the amount of boost in each frequency band. Sliders are those used for controlling the boost or cut. This interface is pretty perceptive because the positions of the sliders themselves resembles the frequency response of the equalizer. The sliders are a graphic representation of the frequency response, hence the name ‘graphic’ equalizer [2]. The actual graphic equalizer implementation is different than the common tone controls. certain frequency bands are attenuated on stereo boost which acts as bass and treble tone knobs while letting everything else pass unaffected, so we can sequence them in series.

G1

G1

BPF1

Input

BPF2

G2

output

Σ

BPF3

G3

BPF L

GL

Figure: Design of Simple Equalizer

A graphic equalizer make use of

a set of bandpass filters that

are intended to completely isolate certain frequency bands. Equalization is the method of varying the frequency response characteristics of a signal. A music equalizer is used to amplify or attenuate a particular band of frequencies of a given signal in order to get better sound effects. The input signal is divided into different frequency bands by a series of bandpass filters (BPF) and then each band is attenuated or boosted by different frequency bands which inturn have independent gain control. All those sliders on the front of the equalizer are the gain controls in each band. The parallel arrangement of Gain factors (G) and all the bands are added

finally to generate a composite signal.

D Parametric Equalizers

Once the signal passes through the bandpass filters, you can now manipulate each of the filters, compared to the series connection with the tone controls, is used to diminish the more harmful effects of the filters. The magnitude frequency responses shown above do not tell us everything about the filter. The filter has a phase response as well. While phase distortion is desirable in some cases , in most sound reinforcement applications, we want to ensure that the sound isn’t colored at all if possible. For each filter you add in series, its phase response is added to the phase response of the other filters. The phase response also reveals how the filter actually delays the signal. If you have two or three filters in your tone control, chaining them in series might be fine, but with a 15 or 31 band graphic equalizer, distortion begins to add up and make a difference.

D Equalization method using Discrete Filters

The audio graphic equalizer has evolved into a set of

filters

at fixed frequencies, covering the audio range.The operator has

has adjusted the level of each individually, either to correct a

magnitude response variation, or to create one intentionally. This degree of control has remained popular despite the recent advances of technology.Digital Signal Processing (DSP) has made it practical to provide many times this resolution to the point where the term arbitrary magnitude response is considered applicable.

As is well known, equalization has phase shift as a mathematical requirement. Phase shift has not always been considered as important as magnitude response because it was less audible. Still, studies have confirmed that it is audible in

some situations.Minimum phase is often chosen for its economy and because it is appropriate for correcting a system with minimum phase characteristics, which may be cancelled by minimum phase filtering without adding time delay. Minimum phase filters might also be appropriate for magnitude correction of system responses with unknown phase characteristics [2]. Although discrete filters can be designed with narrow bandwidths, even approaching a filter shape with a flat top and steep cutoff is expensive,so in practice each filter has an effect over a wider range of frequencies than it is intended to affect. The filter response curves still have significant magnitude at neighboring filter band frequencies. Each band becomes independent, or very nearly so. Otherwise, to be effective, an operator must be very accustomed to the product’s particular filter and combining behavior.

Equalizer filters began as analog second-order filters, and have since been implemented as digital IIR filters. Equalization curves with complex shapes can also be accomplished with single large FIR filters, allowing multiple frequency band settings to be filter significantly affects no more than the first few neighboring frequency bands.

An FIR filter may be designed to approximate the impulse response of many IIR filters, and provides the ultimate in flexibility, where magnitude and phase may be adjusted more specifically and semi-independently. In order to support low frequencies, many thousands of taps are required. In order to economically implement this, complicated methods like multirate processing or the use of FFT for fast circular convolution are used. IIR filters have some advantages over single FIR filters, namely simplicity and speed of design, and better efficiency for a limited number of bands that include low design frequencies. Analog filters are designed once, while a digital filter may need to be redesigned when any parameter changes. Small IIR filters can be adjusted (redesigned) quickly, compared to large FIR filters. Equalizers are usually adjusted manually, but in theory an automated analysis of the sound system may be used[3]. Care then must be taken with correcting no minimum phase responses, where matching the phase requires added delay. Also, equalization of deep notches in the response should not be attempted because of potential adverse effects in other areas of a room, as well as the possibility of amplifier overload. These techniques are also beyond the scope of this paper.

E LabVIEW

LabVIEW is a full-featured graphical programming language

and provides a developed environment for system design(embedded).

LabVIEW is a graphical design tool for development of algorithms, system design (embedded), hardware interference with real world applications. There are different modules introduced to explain the important functionalities of LabVIEW to real-time (scenario) operating systems, DSP, and FPGA programming [2]. By using the LabVIEW as a platform, all the provided functionalities are made possible for signal processing system/ algorithm design and implementation. The LabVIEW helps to install other hardware , drivers toolkits , interfacing its software to provide more support and to provide more compatibility.

functionality and capability. The LabVIEW helps to improve graphical applications and creates a flexible surrounding to interface. A program in LabVIEW is named as Virtual Instrument (VI), which is same as the function called in the C language.

III PROBLEM SOLUTION

There exists a very good concept for the creation of equalizer. The pre-lab study including FIR filter design and its fundamentals helps alot in generating this equalizer. We stared first by clicking on the software (CCStudio V3.1). This now gave us the access to the 6713 chip can also be accessed with the information given in the pre study. Now get the chip connected and then create a new project. And the files according to the program are added to different folders such as the source and library folders. And the scan all dependencies command ,will automatically searches for all the header files in the system and then to the project building of the program is done so that the out file can be generated.The generation of out file is not generated if an error occurs in the program building. DSP board chips will then be loaded with this out file in order to achieve its desired purpose.So here the processing comprising of producing four filters consisting of 1-high-pass , 2-band pass and 1 low pass filters. The low-pass filter has a frequency range of 1300Hz . The first band-pass filter has the range from 1300-2000 hertz . The second bandpass filter has a range between 2000-2800 hertz . Aliasing effect was due to too high order used. Based on FDA tool the filter coefficients were produced in the matlab. FIR filter was measured with window method. Every individual frequency of the filter generates all the filter coefficients. The software was loaded with C-header file generated. The same procedure was followed by different frequencies.

Controlling the different frequency bands by the user graphically is the main aim of the graphic equalizer and providing all frequencies in the signal reducing the distortion. Usually the speech sampling rate is at 8 samples/per sec. Sampling frequency rate is selected at 48KHz so that no aliasing takes place due to higher order. The improper sampling is caused due to aliasing disturbance.If the sampling frequency is less than twice of the input frequency than aliasing takes place. The idea of this project is very simple to get graphical equalization by taking four-band filters1-high pass, 2-band pass and 1-low pass filter. So we have concentrated on this range of frequencies.

For that we have taken four-band filters are low-pass filter

from 1300Hz (Because audible ranges are in the low frequencies, so we have concentrated on the low frequency)and then introduced band pass filter.

In order to increase the resolution the band pass filter can be separated into two filters. So we have separated one band pass into two band pass filters. These are bandpass1, band pass filter2.the first one is band-pass filter1 from 1300-2000Hz, and second one is band-pass filter2 from 2000-2800Hz and after that other frequencies high-pass filter from 2800Hz.

Figure: Graphic Equalizer Template

To get desired transfer function we calculate the filtercoefficients . The equalizer coefficients file consists oftotal filter coefficients of the graphic equalizer. In the coefficient file each set contains (N) coefficients,these coefficients are designed by using MATLAB graphical user interface (GUI) filter designer SPTOOL or MATLAB FDATOOL.

Figure:Block Diagram of Block Equalizer

ACKNOWLEDGMENT

The authors would like to thank Kristen Nilsson for his

valuable guidance and discussions in the accomplishment of

the project.

REFERENCES

[1] Rulph Chassaing and Donald Reay”Digital Signal Processing andApplication with the TMS320C6713 and TMS320C6416 DSK”2nd Ed. pp 125-150

[2] Dr. Woon-Seng S. Gan, Dr. Sen M. Kuo”Embedded Signal Processing with the MicroSignal Architecture,”By c 2006 John Wiley and Sons, Inc.

[3] Ray miller “Equalization methods with true Response using discrete filter ‘Audio’.”Engineering Society Convention Paper 6088.

[4] John G.Proakies, Dimitries G.Manolakis “Digital signal processing Principles, Algorithms, and Applications” 3rd edition pp 629-630.