User:CASE4125
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About Me!
Carolina Capunay was born on September 7, 1989 and grew up in Queens, N.Y. She is eighteen and graduated from Cathedral High School and is currently a freshman at Stony Brook University, majoring in Biology/Pre-Med. She is a part of the WISE program at Stony Brook. Both her parents were born in Peru and came to the U.S., like many parents, with the purpose of providing Carolina with a better future. As a result, Carolina’s parents are her main drive to work hard. She has a younger sister, age twelve. She finds the sciences very interesting, especially biology, and hopes to eventually attend medical school. She enjoys going out, having fun with her friends, movies, dancing, and watching The Fresh Prince of Bel Air with her younger sister. She also enjoys working with kids. She loves music, her family and friends, sarcasm, singing (even though she really can’t), sleep and is obsessed with chocolate! She loves to laugh and believes she has a pretty good sense of humor. In the future, she would like to become a pediatrician and make an impact on the world (big or small!) and possibly travel all over the world! =) She is looking forward to the outcome of the Basic Processing of Radio Signals project.
For more information on WSE 187- Introduction to Research Class WSE 187
Day 1
The first day in the Mariachi Lab consisted of getting familiar with the some of the equipment that we are going to use for our research. Today, we used the WinRadio Reciever and were able to play around with it and see how it works. Our assignment was to find a radio station using this program and record 10 seconds of audio. First, we had to change USB to AM in order to get an AM radio station. Then, the bandwidth and frequency had to be changed a few times until we achieved the AM radio station that we wanted.
Day 2
Today in lab we worked with the software package MATLAB. The MATLAB is a programming language and is used for data visualization. We had to find the command prompt and enter certain numbers. As we worked with the program, we noticed that as when we put these certain numbers, the outcome was a matrix. I learned that entries from a to c created horizontal sequences, while entries d and e created vertical sequences. As we entered more commands, I got more familiar with the program. We were able to produce a 1 x 20 array with a specified location for 1s, in this case, in the 10th and 11th positions. In addition, we were also able to plot a graph of the data produced.
Day 3
Today our task was to generate signals with MATLAB. In order to start, my group had to generate an array from one to zero, with a step of 0.01. The array t, was equal to start:step:stop, and looked like this:
>> t= 0:0.01:1
The next step was to generate a sinusoidal signal y(t): y=sin(2*pi*f*t); f=frequency, while t=the array previously created. Then, this information was plotted by typing in the plot function: plot(t,y). After visualizing this data, we changed the frequency to see if any difference occured. It became known that when the sample signal was divided, the sound decreased; if multiplied, the sound increased.In addition, if the frequency was divided, a lower and longer pitch was produced. However, if the frequency was multiplied a higher and shorter pitch resulted. Also, the greater the f value, the more periods made and the higher the frequency.
After this was done, we moved onto the sound part. In order for this to occur, we used the syntax "sound(sampledSignal,frequency)". First, an array had to be created. After this, we used y(t)=sin(2*pi*440*t). t is equal to the array. We entered (0.5*y(t),8000);y(t)=the signal and 8000=the frequency. When the 0.5 was increased to 2, the signal was much louder then before.
Additive Noise and WAVE File Processing in MATLAB: In this part of the task,we used the function randn, which created a Gaussian noise, represented as an N x M array. Like before, a sound signal was generated. After doing this, the function randn was used to create a noise signal having the same length as the sound signal. Putting this into the sound function resulted in a noise with static. Changing 0.1 to 0.5, we were able to listen to the sound without the static, or Gaussian sound.
Day 4
Today in class, we continued using MATLAB. For today's assignment we learned about WAVE File Saving and Loading. In order to do this, we had to take audio files from the computer and put it into MATLAB, where they were plotted. We used: [readSignal, frequency] = wavread(wavFileName). Using this command, we were able to listen to the audio files with varying frequencies. What I learned today was that the higher the the frequency, the higher the pitch becomes. When a frequency of 8000 was used, a short beep resulted. We had to do the same thing with the file, 2.wav and 3.wav, but with a frequency of 4000, creating a louder beep. An even greater frequency, such as 16000, resulted in a higher. Changing the numbers also affected the length of the sound.
Day 5
For today's task, we used the GUI, or Graphical User Interface, in order to understand how time and frequency affect the sound signals. We were able to then graph this sinusoidal graph. First, we had to load an audio file that we wanted to use. As we changed the frequency, we saw a change in the pitch and length of the audio clip. The greater the frequency the sound seemed to be smaller or compressed and also,the pitch increased. The smaller the frequency made the sound smaller and with a lower pitch. We then noticed that the F1 was related with the periods found in the graph. Looking at the graph, we saw that it contained peaks in the frequency. However the difference between a smaller F1 and a larger F1 is that the peak moves to the left while the other peak moves to the right, respectively. Another fact learned was that when noise level increased, the amplitude increased; yet when the noise decreased, the amplitude decreased.
PROJECT
Today we began our project for this rotation. Because my group was more familiar with Microsoft Excel and thought it was easier than MATLAB, we used Excel to generate our graphs. We were given a folder, C:\wse\project, where we chose a file name. The file we chose was T07121511. We had the function, PdB= 10 x log10(P/P0), which made the file from decibals to not being in decibals. We generated the graphs Signal Power vs. Time (in dB), Signal Power vs. Time(not in dB),Estimated Noise Power vs. Time (in dB), Estimated Noise Power vs. Time (not in dB). As we generated these graphs, we noticed that the graphs in decibals were positive and linear, while the graphs that were not in decibals had other characteristics such as peaks and many jagged edges. Here are two graphs of Signal Strength vs. Time (in decibal and not in decibal):
We continued with the project by completing Task Two and Three. At this point, we used a combination of MATLAB. I can say that out of all the days, I learned the most on the last day! Today, my group and I worked quicker and without alot of help, as we needed before. I understood what commands to right and the reasons as to why the graph came out like they did. I am glad that I finally grasped the concepts fully, even though it was on the last day; that was the purpose of this rotation, to complete it with new acquired knowledge from our experiences here at the NSL Lab. We continued using Excel and found it very easy, at this point, to produce the 1s and 0s. We did this by typing in the command: [=f(C1-6>D1,1,0]. This meant that if C1, after being subtracted by 6, was less than D1, then it would be a 1. If this was not the case, then it would be 0. We then had to change the pattern of the first 1s and 0s and used the formula, [=if(and(H1=0,H2=1),1,0)] to do so. Because we had so many numbers, it was impossible to count them in a quick manner, so we used the command:[=sum(F1:Fx]. The gave us the SUM function on Excel and was able to count how many indicators there were. In this case, there was 37. We used the same methods on another file, file T07121500, which generated 31.
