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Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
Digital Tuner Project Final Report
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Digital Tuner Project Final Report

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Final report for our Digital Tuner Project at TU Berlin. We built and programmed a digital music

Final report for our Digital Tuner Project at TU Berlin. We built and programmed a digital music

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  • 1. Digital Tuner Project TU Berlin – Summer 2012 Mihir ,Jennifer Liu, Samantha Luber, Michael UlrichI. Introduction The Digital Tuner Project consists of building a tuner board that accepts sound signals through a microphone as input, performs signal processing and analysis on the sound signal, and outputs the corresponding guitar note and the guitar note’s “in tune-ness” via LED lights as output. This report contains a detailed description of the Digital Tuner’s hardware and programming implementation in addition to the signal sampling and processing theory behind the project. A. Digital Tuner Board Overview The Digital Tuner Board is a device that analyzes the spectrum of a sound signal and determines the corresponding guitar string and whether or not the string is in tune, sharp, or flat. The project consists of four stages: building the board, implementing an analog-to-digital converter, performing digital signal processing on the signal, and developing and implementing an algorithm for determining the note and tune of the sound signal [1]. This section provides an overview of the hardware and software components utilized in the project and the significance of the project’s underlying theoretical components to the signal and microprocessor fields of study. B. Project Tools This subsection consists of a brief overview of the hardware and software components utilized in the Digital Tuner Board project. 1. Hardware Components The Digital Tuner Project consisted of hardware for the Digital Tuner Board itself as well as hardware for testing the board. Described in detail in the Digital Tuner Board Hardware section and Appendix A., notable hardware components in the Digital Tuner Board includes the ATmega1284P processor, the microphone, and USB to UART transmitter. Hardware for building and testing the Digital Tuner includes a soldering iron, an oscilloscope, a multimeter, and a wave function generator. 2. Software Components Software used in the Digital Tuner Project includes MATLAB and AVRStudio. MATLAB was used for testing algorithms for performing Fourier transforms on signals, calculating frequency spectrum of signals, and analyzing and verifying the output of the analog-to-digital converter implementation in the micro-controller. AVRStudio is an IDE for micro-controller programming and was used for programming the Digital Tuner Board and flashing code to the board. C. Relevance The Digital Tuner is relevant to the fields of signal and microprocessor study because it encapsulates the theoretical components of the digital measurement
  • 2. chain, intelligent sensors, and frequency analysis [1]. Throughout the project, hardware building, digital measurement technology, signal processing, and micro-controller programming is learned and utilized.II. Digital Tuner Board Hardware The section contains details of the hardware components, the hardware layout, and hardware testing of the Digital Tuner Board. A. Hardware Overview Shown below in Figure 1, the Digital Tuner Board consists of a series of hardware components, described in detail in Appendix A., including resistors, capacitors, LED lights, a crystal oscillator, a potentiometer, operational amplifiers, a USB to UART transmitter, and an ATmega1284P micro- controller. Figure 1. The Digital Tuner Board. This figure shows a fully constructed Digital Tuner Board, built through soldering hardware components to a basic board [1]. The ATmega1284P is an 8-bit Atmel micro-controller with 32 general- purpose I/O lines (PORTA-PORTD) and two USARTs for serial communication with peripherals [2]. B. Soldering All components of the Digital Tuner Board were attached using Tin Lead solder and standard soldering techniques. The recommended assembly order for the board used included attaching hardware components in the following order: • Resistors, capacitors • SMD parts • EMI filter • LEDs • Crystal Oscillator • Push-buttons • IC Sockets • Micro-controller • Microphone
  • 3. The full board circuitry layout and schematic can be found in Appendix A. C. Hardware Testing Hardware testing of the Digital Tuner Board consists of general testing and filter testing. General testing includes applying and measuring various voltages across the IC pins and LED’s. Filter testing includes using the oscilloscope to verify the low-pass filter implemented on the board. Figure 2 shows the validated frequency response from the low pass filter of the Digital Tuner Board. Figure 2. Frequency Response of the Low Pass Filter. This figure shows the frequency response of the Digital Tuner Board’s low pass filter. The blue line shows the frequency response of the input signal. The red line shows the frequency response of the output signal from the low pass filter. As the filter cuts off frequencies below the designated cutoff frequency, the low pass filter of the Digital Tuner Board can be validated. Final testing includes connecting the microphone to the system via jumper pins and watching for sound signal output measured via the oscilloscope. Once hardware construction and testing is complete, the project moves on to sampling and analysis of guitar sound signals.III. Theoretical Music Note Analysis This section contains an overview of the digital measurement technology and digital signal theories prevalent throughout the Digital Tuner Board Project. A. Understanding the Digital Measurement Chain The digital measurement chain consists of a series of steps required to effectively perform digital signal processing on an input signal. Figure 3 shows a diagram of each step of the Digital Measurement Chain specific to the Digital Tuner Project.
  • 4. Figure 3. The Digital Measurement Chain. This flowchart depicts each stage in the Digital Measurement Chain as it is used in the Digital Tuner Project, beginning with the initial capture of the input signal at the microphone and ending with LED output resulting from digital signal processing on the signal [1]. Corresponding to the elements in Figure 3, the general stages of the Digital Measurement Chain include signal input, signal conditioning, anti-aliasing, signal sampling, analog-to-digital conversion, digital signal processing, and output [3]. Described in detail in Appendix B., each stage in the Digital Measurement Chain is essential for a correct interpretation of an input signal. B. Theory of Digital Signal Processing After the input analog signal is conditioned and converted into a digital signal, the Digital Tuner performs various processes for analysis. Described in detail in Appendix C., the micro-controller converts the digital signal into an amplitude spectrum in the frequency domain. In this state, the maximum amplitude peak for the captured signal can be quickly determined. The frequency corresponding to this amplitude peak is the calculated frequency of the input guitar signal [4]. Using this information, further calculations can be performed specific to the analysis of the guitar note frequency.IV. Digital Tuner Board Implementation This section contains an overview of the micro-controller code implementation for the Digital Tuner Board, including a program flowchart, design implementation decisions, and an overview of the user interface for the Digital Tuner Board. Appendix D. includes a detailed description of the program’s modules as well as the serial communication, interrupt, and timing subsystems of the micro-controller, all of which are used in the Digital Music Tuner code implementation. A. Concept Overview The Digital Tuner program runs continuously, waiting for user input and producing output accordingly. The flow chart of the Music Tuner system, including the micro-controller program, is shown below in Figure 4.
  • 5. Figure 4. Digital Tuner Program Flow Chart. This flow chart shows the various states of the Digital Tuner.When a guitar string is played, if the analog-to-digital converter (ADC) isnt alreadyrunning, the ADC is triggered by the rising edge of the input signals frequency. TheADC can also be started via messages over the micro-controllers bus line using USART[5]. Once the ADC starts running, a specified number of samples is collected from theinput signal and quantized into a digital signal [6]. The ADC concept and implementationis described in detail in Appendix E. Once the conversion is complete, the micro-controller does further processing on the digital signal, described in detail in Appendix C.First, the a Fourier transformation is applied to the digital signal and an amplitudespectrum is calculated, as shown in Figure 5a [2].
  • 6. Figure 5a. Amplitude Spectrum of an Input Signal. This figure shows the amplitude spectrum of an inputguitar signal. The peak amplitude in the spectrum corresponds to the frequency of the guitar string beingplayed, as shown in Figure 5b.Next, the largest amplitude in the spectrum is determined along with its correspondingfrequency. This frequency value is the calculated frequency of the input guitar string.Using fixed ranges of frequency values to guitar note and tune correspondence, as shownin Figure 5b below, the guitar note and whether the note is in tune, flat, or sharp isdetermined.Signal  Frequency  (Hz)   Guitar  Note  82.41   Low  E  110.0   A  146.8   D  196.0   G  246.9   B  329.6   High  E   Figure 5b. Signal Frequency to Guitar Note Chart. This chart shows the correspondence between input signal frequency and guitar note. The micro-controller uses this chart with additional ranges for flatness and sharpness to calculate the correct LED output.LED’s are updated to reflect these calculations and communicate with the user.Implementation details and code excerpts can be found in Appendix D. B. User Interface Overview The User Interface of the Digital Tuner Board consists of six LED lights to provide user feedback. Shown below in Figure 6, Each LED light corresponds
  • 7. to a string on the guitar with the left-most LED light representing the low E note and the right-most LED light representing the high E note. Figure 6. LED User Interface. This figure shows the user interface of the Digital Tuner Board. The LED lights (labeled by pin numbers PB4-PB0 and PD7) represent the corresponding guitar strings displayed above. To represent the tune of each guitar note, LED’s blink to the left or right of the lit guitar note LED light. For example, in reference to Figure 6 above, if a very flat D guitar string is played, the Low E and A LED lights will blink. Similarly, if a somewhat flat D guitar string is played, only the A LED light will flash. This same process is used for indicating sharp notes by blinking LED’s to the right of the out-of-tune note. In the event that the Low E note is flat or the High E note is sharp, the blinking LED’s “wrap around” to the other side of the LED lights.V. Conclusion The Digital Tuner Project provided an interactive learning environment for building hardware by soldering, signal sampling, analog-to-digital signal conversion, Fourier transformation of signals, signal spectrum analysis, micro-controller programing in C, and user interface development [1].VI. Acknowledgments Special thanks to Joachim Priesnitz, Jürgen Funck, and Andreas Bock for holding open lab hours to provide support and debugging assistance with the Digital Tuner Project.VII. Appendix A. Hardware Components This appendix contains a detailed description of the hardware components included in the Digital Tuner Board. A. Atmega1284P Micro-controller The Atmega1284P is an 8-bit micro-controller with 32 I/O pins, 32 general- purpose registers, three flexible Timer/Counters, and Flash memory. The board supports communication via USART and SPI [2]. Figure 7 below shows the block diagram of the Atmega1284P micro-controller.
  • 8. Figure 7. Atmel Atmega1284P Micro-controller [2].B. Digital Tuner Board Circuitry DiagramFigure 8 below shows the circuitry diagram of the Digital Tuner Board.
  • 9.  Figure 8. Digital Tuner Board Circuitry Diagram [7].C. Tuner Board SchematicsFigure 9 below shows the schematics of the Digital Tuner Board.
  • 10.   Figure 9. Digital Tuner Board Schematics [7]. VIII. Appendix B. Measurement TechnologyThis appendix contains a detailed description of the components of the DigitalMeasurement Chain. The digital measurement chain consists of five stages: signalconditioning, anti-aliasing, sample & hold, analog-to-digital conversion, and dataprocessing. A. Signal ConditioningSignal conditioning involves adjusting the input signal for more accurate analysis. Thisstage typically involves using operational amplifiers to magnify the signal [3]. TheDigital Tuner Board has an operational amplifier for this purpose. B. Anti-aliasingThe anti-aliasing stage is responsible for removing erroneous signals in the input signal,resulting from aliasing in the signal sampling. Low-pass filters are typically used to filterout these artifacts [3]. The Digital Tuner Board has a low-pass filter used in this anti-aliasing stage. C. Sample & HoldThe sample and hold stage includes capturing the data of an input signal and accepting nonew input until data processing on the captured data is complete. D. Analog-to-Digital ConversionThe Analog-to-Digital Converter (ADC) converts an analog signal to a digital signal. Theaccuracy of the ADC is dependent on the converters resolution. An ADC with lowresolution typically produces an output digital signal with a significant amount ofquantization error [3]. E. Data ProcessingThe data processing stage includes advanced processing of the digital signal by themicro-controller. In the Digital Tuner Board, the amplitude spectrum of the digital signal
  • 11. is computed and analyzed in this stage to determine the guitars note and tune. IX. Appendix C. Signals and Sampling TheoryThis appendix contains a brief overview of theoretical and practical signal sampling, theFourier transformation, and amplitude spectrum analysis as well as their application tothe Digital Tuner Project. A. Signal SamplingWhen sampling an analog signal, using an appropriate sample rate is essential forreconstructing the input signal accurately. Theoretically, sampling a signal faster than theNyquist Rate, or twice the maximum frequency of the input signal, is sufficient foraccurate sampling [3]. However, in real-world applications, sampling must take place at amuch higher rate due to inaccuracies of electrical components. When a signal is notsampled fast enough, aliasing, or the introduction of noise and erroneous artifacts into theinput signal, can occur. B. The Fourier TransformationThe Fourier Transformation is a mathematical procedure for converter signals in the timedomain to signals in the frequency domain. In the frequency domain, analysis of signalsis often simpler as periodic signals are represented by pulses instead of continuoussignals [4]. For algorithm verification, the Digital Tuner Board implementation of theFourier transform and inverse Fourier transform was first written and tested in Matlab.Below are code excerpts of both functions. 1. Fourier Transform MATLAB Code function [x] = fourier_transform(signal, N) x = zeros(N, 1); for k = 1:N for n = 1:N x(k) = x(k) + signal(n)*exp(-1i*(n-1)*(k-1)*2*pi/N); end end plot(x) end 2. Inverse Fourier Transform MATLAB Code function  [x]  =  inverse_ft(X,  N)   x  =  zeros(N,  1);   for  n  =  1:N        for  k  =  1:N              x(n)  =  x(n)  +  X(k)*exp(i*(n-­‐1)*(k-­‐1)*2*pi/N);        end        x(n)  =  (1/N).*x(n);   end   end   C. Amplitude Spectrum AnalysisIn order to determine the guitar note and tune of the input frequency, the amplitudespectrum of the input frequency must be analyzed. A maximum frequency functioncalculates the frequency in the amplitude spectrum at which the amplitude is at amaximum by iterating through all of the amplitude values. A special case is made forlower guitar strings as resonance at this frequencies can occur.
  • 12. X. Appendix D. Micro-controller Programming SpecificationsThis appendix includes a detailed description of the program’s modules as well as theserial communication, interrupt, and timing subsystems of the micro-controller, all ofwhich are used in the Digital Tuner code implementation. A. Digital Tuner Program ModulesThe Digital Tuner program consists of five modules: serial communication, analog-to-digital conversion, Fourier transformation, digital signal processing, and I/O. Serialcommunication allows the micro-controller to communicate with peripherals via USART.The analog-to-digital converter converts input analog signals to digital signals. TheFourier transformation module generates the amplitude spectrum of the sampled signal.The digital signal processing stage determines the guitar note and tune. The I/O moduleconsists of the microphone (input) and the LEDs (output). B. Serial Communication SystemThe Atmega1284P micro-controller supports serial communication over USART. Fortesting and debugging purposes, output from the board can be sent over USART toMATLAB or another peripheral for verification. The Digital Tuner Board establishes atwo-way communication channel with the computer, such that it can both send andreceive messages. The specific USART configurations for the Digital Tuner Boardinclude a 115200 baud rate and 8 data bit messages with 1 stop bit and no parity. USARTis a widely used serial communication system that allows data to be transmitted bothsynchronously and asynchronously over a bus line. Advantages of USART includesimplicity and the need for only one or two data lines. A significant drawback of USARTis the slow communication rate, as data bits are transferred one at a time over the bus line[5]. Below are code excerpts for sending and receiving data via USART. Note that aninterrupt, described in detail in the follow subsection, is triggered when a data bit isreceived on the bus line.void USART_transmit(unsigned char data) { /* Wait for empty transmit buffer */ while (!( UCSR1A & (1<<UDRE1))); /* Put data into buffer, sends the data */ UDR1 = data; } /*** INTERRUPT ROUTINES ***/ ISR(USART1_RX_vect) { char data = (char)UDR1; } C. Interrupt SubsystemThe Atmega1284P micro-controller supports interrupts, a system for handling high-priority events. Interrupts are triggered by per-defined events. When an interrupt occurs,the executing program is paused, the state of the machine is saved, and the micro-controller begins executing the interrupt handler routine associated with the interrupt.Once the interrupt routine is complete, the micro-controller restores the state of themachine and resumes the executing program [8]. In the Digital Tuner Board, interruptsare used to pause the executing program when a message is received over USART or asample is converted in the ADC.
  • 13. D. Timing SubsystemThe time subsystem of the Atmega1284P is essential for serial communication and signalsampling. The crystal oscillator on the board oscillates and generates a clock. This clockcan be adjusted to run at a desired rate. In order to communicate with peripherals overUSART, the clock must be adjusted such that bits are sent at the correct rate.Furthermore, in order to achieve the desired signal sample rate, the clock must beadjusted to allow for correct sampling of the signal [9]. XI. Appendix E. Analog-To-Digital ConverterThis appendix contains a detailed description of the Digital Tuner Boardsimplementation and testing.A. Configuring the Analog to Digital ConverterIn order to convert analog input signals to digital signals on the Music Tuner board, wehave implemented an Analog to Digital Converter with the following specifications: ▪ AREF-Pin for voltage reference ▪ Single-ended input on channel ADC0 ▪ ADC-Clock running at 1/64 of the CPU-Clock ▪ ADC conversions beginning with Auto-Triggering • Each new conversion starting with a Compare-Match-Interrupt B on Timer1 These settings are configured for desired digital signal output, specific to the Music Tuner board.B. Implementing the Analog to Digital ConverterThe Analog to Digital Converter consists of four functions: adcInit, adcStart,adcIsRunning, and an interrupt function (ADC_vect). The specifications of the functionimplementations are as follows.1. Analog to Digital Converter Initationation FunctionThe adcInit() function is responsible for initializing the ADC and setting thecorresponding registers to the desired settings.void adcInit() { // Set voltage to AFREF-Pin as a voltage reference (default) // Sets ADC Enable to On, Initates an ADC, Enables Auto-Triggering, Enables interrupts ADCSRA = (1<<ADEN) | (1<<ADATE) | (1 << ADPS2) | (1 << ADPS1) |(0 << ADPS0); // Sets ADC-Clock to Fclk/64 ADCSRB = (1 << ADTS2) | (0 << ADTS1) | (1 << ADTS0);}2. Analog to Digital Converter Start FunctionThe adcStart() function is responsible for initiating an ADC conversion of the inputsignal.void adcStart(uint16_t sampleRateCode, uint16_t sampleCount, trigger_t triggerMode, int16_t triggerLevel,int16_t* adcBuf) { // Put Timer1 in CTC mode with CPU clock and no prescaling TCCR1B = (1<<WGM12) | (0<<CS12) | (0<<CS11) | (1<<CS10); TIMSK1 = (1<<OCIE1B) | (1<<OCIE1A); OCR1A = sampleRateCode; OCR1B = sampleRateCode; sample_rate = sampleRateCode; trigger = triggerMode; trigger_level = triggerLevel; samples_aquired = 0; samples_needed = sampleCount;
  • 14. adcBuf2 = adcBuf; sei(); //Enable interrupts ADCSRA |= (1 << ADIE);}3. Analog to Digital Converter Running FunctionThe isADCRunning() function is responsible for returning whether or not the number ofsamples taken is equal to the number of samples required. In other words, theisADCRunning() function returns whether or not the ADC is running.uint8_t adcIsRunning() { return (samples_aquired < samples_needed && samples_needed != 0);}4. Analog to Digital Converter Sample Available Interrupt FunctionThe interrupt function handles reading the output of the ADC for each sample. Thisfunction is called upon completion of a sample conversion./** * fn ISR(ADC_vect) * author your_name * date day_of_implementation * brief Interrupt-Routine for the ADC-Interrupt. * Gets called when an analog-to-digital conversion is complete */ISR(ADC_vect) { // Check if ADC triggered switch(trigger){ case RISING: if (!adcIsRunning() && prev_value < trigger_level && ADC > trigger_level) { adcStart(sample_rate, samples_needed, trigger,trigger_level, adcBuf2); } break; case FALLING: if (!adcIsRunning() && prev_value > trigger_level && ADC < trigger_level) { adcStart(sample_rate, samples_needed, trigger,trigger_level, adcBuf2); } break; default: break; } // Read conversion result and write to buffer adcBuf2[samples_aquired] = ADC-512; prev_value = ADC-512; samples_aquired++; // Stop if desired samples reached if (!adcIsRunning()) { ADCSRA &= ~(1<<ADIE); }}C. Validating the Analog to Digital ConverterIn order to validate the accuracy of our Analog to Digital Converter, we have performed aseries of tests of various input signals to the ADC.1. Constant Input SignalIn order to verify the output of our ADC, we sent various analog DC voltage signals inthe range of 0 to 3.3 volts to our Music Tuner board. We ran the ADC on these inputsignals with a sample frequency of 1kHz for 1000 samples with the trigger mode
  • 15. disabled. Our expected output was to see output results that are approximately the samefor all 1000 samples because the DC sample signals are all of the same voltage.Furthermore, we expected to see higher output results as the input signal voltageincreased [6]. Consistent with these expectations, we saw approximately uniform outputvalues for our input signals that increased as the input signal voltage increased. Forexample, with an input signal of 2.69 volts, our mean output value was 831.6040. Basedon our observations, we can see that our ADC is performing as expected (correctly).2. Triangle Input SignalIn addition to testing our ADC system with a constant DC input voltage, we also testedour ADC with a triangle signal, ranging from 0 to 3.3 volts). We expected to see outputresults consistent with the shape of this input signal. Our results are shown below inFigure 10.Figure 10. Analog to Digital Converter Output from a Triangular Input Signal. Thisgraph demonstrates the ADC output from an inputted triangle signal. Consistent with ourexpected output of the ADC, the shape of the output resembles that of the input inquantized form.
  • 16. Figure 11 Amplitude Spectrum of the ADC output from a triangular input signal. Thisgraph shows the amplitude spectrum of the ADC output displayed in Figure 10. Furtherverifying the accuracy of our ADC, we can see that this amplitude spectrum, achievedthrough fourier transformation of the ADC output values, is consistent with the amplitudespectrum of a triangular signal.Based on the close resemblance of our ADC output signal to the original triangular inputsignal in both the time and frequency domain, we can confirm that our ADC isperforming conversions correctly for triangular input signals.3. Sine Input SignalIn addition to testing our ADC system with a constant DC input voltage and triangularsignal, we also tested our ADC with a sinusoidal signal, ranging from 0 to 3.3 volts). Weexpected to see output results consistent with the shape of this input signal [6]. Ourresults are shown below in Figure 12.
  • 17. Figure 12. Analog to Digital Converter Output from a Sinusoidal Input Signal. Thisgraph demonstrates the ADC output from an inputted sine signal. Consistent with ourexpected output of the ADC, the shape of the output resembles that of the input inquantized form.Figure 14. Amplitude Spectrum of the ADC output from a sinusoidal input signal. Thisgraph shows the amplitude spectrum of the ADC output displayed in Figure 12. Furtherverifying the accuracy of our ADC, we can see that this amplitude spectrum, achievedthrough fourier transformation of the ADC output values, is consistent with the amplitudespectrum of a sinusoidal signal.
  • 18. Based on the close resemblance of our ADC output signal to the original triangular inputsignal in both the time and frequency domain, we can confirm that our ADC isperforming conversions correctly for triangular input signals. Through our ADCimplementation and testing, we have created and verified a system for reliably convertinganalog input signals to digital signals in order to perform further digital signal processingon these input signals [6]. Specific to our project’s applications, we have created a systemfor inputting sound signals from playing notes on a guitar and converting these soundsignals into a digital representation with the ultimate goal of determining the frequencyand corresponding guitar music note of these inputted sound signals. XII. References 1. Gühmann, Clemens, Phd. IESS 2012 – The Digital Tuner Project. Technische Universität Berlin. 2. ATmega1284P. Atmel Corporation. <http://www.atmel.com/devices/atmega1284p.aspx>. 3. Gühmann, Clemens, Phd. Introduction to Measurement Technology. Technische Universität Berlin. 4. Gühmann, Clemens, Phd. Time-discrete Signals in the Frequency Domain. Technische Universität Berlin. 5. Serial Communication Subsystem. Technische Universität Berlin. 6. Analog-to-Digital Conversion. Technische Universität Berlin. 7. Bock, Andreas. Assembly Guide for the Guitar Tuner. Technische Universität Berlin. 8. Interrupt Subsystem. Technische Universität Berlin. 9. Timing Subsystem. Technische Universität Berlin.

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