用地道英文表达方式润色下面的英文We have studied reviewers’ comments carefully. According to the reviewers’ detailed suggestions, we have made a careful revision of the original manuscript. All revised portions are marked in red in the revised manuscript which we would like to submit for your kind consideration.
时间: 2024-04-22 08:23:58 浏览: 186
We have thoroughly reviewed the reviewers' comments and have taken them into careful consideration. As per their detailed suggestions, we have diligently revised the original manuscript, with all revised sections being clearly indicated in red within the updated manuscript that we hereby submit for your kind consideration.
相关问题
A = imread('krabi1.bmp','BMP'); %read in the image A_shrunk = imresize(A,0.2); % we’ll reduce the resolution, as otherwise the file size is too large imshow(A_shrunk) % displays the shrunken image Bs = reshape(A_shrunk,[388*518*3,1,1]); % resizes this image from a pixel array of three colours to a one-dimensional data stream C = de2bi(double(Bs)); % converts these values to binary representation % You can then resize this array to a linear, one-dimensional array. % this data stream C is then what you can communicate over your channel. % recover the image from the binary sequence BS_rec = uint8(bi2de(C)); % convert bits to pixel values. A_rec = reshape(BS_rec,[388,518,3]); % reshape back to a coloured pixel array. imshow(A_rec) % display the recovered image. Explore the pskmod and pskdemod commands in MATLAB. Use these to modulate and demodulate the binary sequence into a binary PSK signal. (Hint: the command should be something like D = pskmod(C,2). Display a part of this signal, and explain carefully how we have represented this signal in MATLAB, and how it differs from the analysis we performed in Part A. Transmit this signal through an AWGN channel using the awgn() function for a range of signal to noise ratios. Demodulate and comment on the effect of the noise on the image. A suitable range of signal to noise ratios is –0.5dB to 5 dB. The bit error rate refers to the fraction of bits that are received in error. This can also be interpreted as the probability that a bit is received in error. Calculate the bit error rate (BER) for the signal to noise ratios you used above. Comment on the correlation between BER and perceptual image quality. Now apply channel coding to the transmitted data sequence. Use encode(msg,7,4,’hamming’), encode(msg,15,7,’bch’), and convenc, following the example listed in the help window (recall, in MATLAB type “help convenc” to obtain the help information for that command. For each of these codes, study how the code can reduce the BER and improve image quality for each SNR you studied above.
这是一个关于数字图像处理和通信的问题,需要一些MATLAB知识。下面是对问题的回答:
1. 读入并压缩图像
首先,使用`imread`函数读入一张图片,并使用`imresize`函数将图片压缩到原来的20%大小:
```
A = imread('krabi1.bmp', 'BMP');
A_shrunk = imresize(A, 0.2);
```
2. 将图像转换为一维数据流
将压缩后的图像重新排列为一维数据流,以便进行数字通信。使用`reshape`函数将3通道的像素矩阵转换为一维列向量,并使用`de2bi`函数将像素值转换为二进制表示:
```
Bs = reshape(A_shrunk, [388*518*3, 1, 1]);
C = de2bi(double(Bs));
```
3. 二进制PSK调制
使用`pskmod`函数将二进制数据流进行相位调制,生成二进制PSK信号。例如,调制成二进制PSK2:
```
D = pskmod(C, 2);
```
4. 加入高斯白噪声
使用`awgn`函数将二进制PSK信号加入高斯白噪声,模拟通信信道的影响。例如,将信噪比设置为0dB:
```
noisy_D = awgn(D, 0, 'measured');
```
5. 二进制PSK解调
使用`pskdemod`函数将接收到的二进制PSK信号解调回二进制数据流:
```
rec_C = pskdemod(noisy_D, 2);
```
6. 解码并恢复图像
使用`bi2de`函数将二进制数据流转换为像素值,然后使用`reshape`函数将像素值重新排列为3通道的像素矩阵,最后使用`imshow`函数显示恢复后的图像:
```
rec_Bs = uint8(bi2de(rec_C));
A_rec = reshape(rec_Bs, [388, 518, 3]);
imshow(A_rec);
```
7. 计算误码率
使用`biterr`函数计算解调后的数据流和原始数据流之间的误码率,并根据不同信噪比的误码率绘制误码率曲线:
```
ber = zeros(1, length(snr));
for i = 1:length(snr)
noisy_D = awgn(D, snr(i), 'measured');
rec_C = pskdemod(noisy_D, 2);
ber(i) = biterr(C, rec_C) / length(C);
end
semilogy(snr, ber);
```
8. 应用通道编码
使用`encode`函数对二进制数据流进行通道编码,对比不同编码方案的误码率曲线和图像质量:
```
% Hamming(7,4)编码
hamming_encoded = encode(C, 7, 4, 'hamming');
hamming_D = pskmod(hamming_encoded, 2);
hamming_noisy_D = awgn(hamming_D, snr(i), 'measured');
hamming_rec_C = pskdemod(hamming_noisy_D, 2);
hamming_rec_Bs = uint8(bi2de(hamming_rec_C));
hamming_A_rec = reshape(hamming_rec_Bs, [388, 518, 3]);
hamming_ber(i) = biterr(C, hamming_rec_C) / length(C);
% BCH(15,7)编码
bch_encoded = encode(C, 15, 7, 'bch');
bch_D = pskmod(bch_encoded, 2);
bch_noisy_D = awgn(bch_D, snr(i), 'measured');
bch_rec_C = pskdemod(bch_noisy_D, 2);
bch_rec_Bs = uint8(bi2de(bch_rec_C));
bch_A_rec = reshape(bch_rec_Bs, [388, 518, 3]);
bch_ber(i) = biterr(C, bch_rec_C) / length(C);
% 卷积编码
trellis = poly2trellis(7, [171 133]);
conv_encoded = convenc(C, trellis);
conv_D = pskmod(conv_encoded, 2);
conv_noisy_D = awgn(conv_D, snr(i), 'measured');
conv_rec_D = pskdemod(conv_noisy_D, 2);
conv_rec_C = vitdec(conv_rec_D, trellis, 15, 'trunc', 'hard');
conv_rec_Bs = uint8(bi2de(conv_rec_C));
conv_A_rec = reshape(conv_rec_Bs, [388, 518, 3]);
conv_ber(i) = biterr(C, conv_rec_C) / length(C);
```
需要注意的是,以上代码仅供参考,具体实现还需要根据实际情况进行调整。
Develop a NetBeans application that illustrates the applicability of one sorting algorithm on a collection of 10 items. The algorithm should sort the items in descending order. The algorithm must work based on the principle of one of the four sorting algorithms studied during the semester. The collection of 10 items is defined and populated in the application code. You can decide the type and values of items stored in the collection. The algorithm must be implemented as part of a class called MyArrayList that extends the ArrayList class functionality with your sorting algorithm. [20 marks] 5. Extend the application implemented for Question 4 above to be able to measure the efficiency of the implemented sorting algorithm in term of number of comparisons performed by the algorithm. The application should display the total number of comparisons performed by the algorithm for a given collection of items. [10 marks] 6. In an Excel graph, plot the number of comparisons measured by the sorting algorithm when three different sizes of collection are considered. Submit your Excel file on Moodle. [20 marks]
Sure, I understand your question. You want me to develop a NetBeans application that demonstrates the use of one sorting algorithm on a collection of 10 items, sorting them in descending order. The algorithm should be based on one of the four sorting algorithms studied during the semester and should be implemented as part of a class called MyArrayList that extends the ArrayList class functionality with your sorting algorithm. Additionally, you want me to extend the application to measure the efficiency of the implemented sorting algorithm in terms of the number of comparisons performed by the algorithm, and to plot the number of comparisons measured by the sorting algorithm when three different sizes of collection are considered in an Excel graph.
To start, let's define and populate the collection of 10 items in the NetBeans application code. We can use integers for the items stored in the collection. Here's an example of how the collection can be defined and populated:
```
import java.util.ArrayList;
public class SortingDemo {
public static void main(String[] args) {
MyArrayList<Integer> list = new MyArrayList<Integer>();
list.add(5);
list.add(2);
list.add(10);
list.add(8);
list.add(1);
list.add(7);
list.add(9);
list.add(3);
list.add(4);
list.add(6);
System.out.println("Original list: " + list);
list.sortDescending();
System.out.println("Sorted list: " + list);
}
}
class MyArrayList<E extends Comparable<E>> extends ArrayList<E> {
public void sortDescending() {
// Insertion sort algorithm
for (int i = 1; i < size(); i++) {
E key = get(i);
int j = i - 1;
while (j >= 0 && get(j).compareTo(key) < 0) {
set(j + 1, get(j));
j--;
}
set(j + 1, key);
}
}
}
```
In the above code, we define a class called SortingDemo which contains a main method. Inside the main method, we create an instance of MyArrayList and add 10 integers to it. We then print out the original list and call the sortDescending method on the list to sort it in descending order. Finally, we print out the sorted list.
The MyArrayList class extends the ArrayList class and defines a sortDescending method that implements the insertion sort algorithm to sort the list in descending order.
Next, we need to extend the application to measure the efficiency of the sorting algorithm in terms of the number of comparisons performed by the algorithm. We can modify the MyArrayList class to keep track of the number of comparisons performed during the sorting process, like this:
```
class MyArrayList<E extends Comparable<E>> extends ArrayList<E> {
private int comparisons;
public void sortDescending() {
comparisons = 0;
// Insertion sort algorithm
for (int i = 1; i < size(); i++) {
E key = get(i);
int j = i - 1;
while (j >= 0 && get(j).compareTo(key) < 0) {
set(j + 1, get(j));
j--;
comparisons++;
}
set(j + 1, key);
}
}
public int getComparisons() {
return comparisons;
}
}
```
We added a private variable called comparisons to keep track of the number of comparisons performed during the sorting process. We initialize it to 0 at the start of the sortDescending method and increment it for each comparison performed. We also added a public method called getComparisons to retrieve the number of comparisons performed.
Finally, we need to plot the number of comparisons measured by the sorting algorithm when three different sizes of collection are considered in an Excel graph. To do this, we can modify the SortingDemo class to create three different lists of different sizes and sort each of them, recording the number of comparisons performed for each sort. We can then export the data to an Excel file and create a graph with the data.
Here's an example of the modified SortingDemo class:
```
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import org.apache.poi.ss.usermodel.Cell;
import org.apache.poi.ss.usermodel.Row;
import org.apache.poi.xssf.usermodel.XSSFWorkbook;
public class SortingDemo {
public static void main(String[] args) {
MyArrayList<Integer> list1 = new MyArrayList<Integer>();
list1.add(5);
list1.add(2);
list1.add(10);
list1.add(8);
list1.add(1);
list1.add(7);
list1.add(9);
list1.add(3);
list1.add(4);
list1.add(6);
System.out.println("Original list 1: " + list1);
list1.sortDescending();
System.out.println("Sorted list 1: " + list1);
int comparisons1 = list1.getComparisons();
MyArrayList<Integer> list2 = new MyArrayList<Integer>();
for (int i = 0; i < 100; i++) {
list2.add((int) (Math.random() * 100));
}
System.out.println("Original list 2: " + list2);
list2.sortDescending();
System.out.println("Sorted list 2: " + list2);
int comparisons2 = list2.getComparisons();
MyArrayList<Integer> list3 = new MyArrayList<Integer>();
for (int i = 0; i < 1000; i++) {
list3.add((int) (Math.random() * 100));
}
System.out.println("Original list 3: " + list3);
list3.sortDescending();
System.out.println("Sorted list 3: " + list3);
int comparisons3 = list3.getComparisons();
System.out.println("Comparisons 1: " + comparisons1);
System.out.println("Comparisons 2: " + comparisons2);
System.out.println("Comparisons 3: " + comparisons3);
try (XSSFWorkbook workbook = new XSSFWorkbook()) {
FileOutputStream out = new FileOutputStream(new File("sorting.xlsx"));
org.apache.poi.ss.usermodel.Sheet sheet = workbook.createSheet("Sorting");
Row headerRow = sheet.createRow(0);
Cell cell0 = headerRow.createCell(0);
cell0.setCellValue("Collection Size");
Cell cell1 = headerRow.createCell(1);
cell1.setCellValue("Comparisons");
Row row1 = sheet.createRow(1);
Cell cell10 = row1.createCell(0);
cell10.setCellValue("10");
Cell cell11 = row1.createCell(1);
cell11.setCellValue(comparisons1);
Row row2 = sheet.createRow(2);
Cell cell20 = row2.createCell(0);
cell20.setCellValue("100");
Cell cell21 = row2.createCell(1);
cell21.setCellValue(comparisons2);
Row row3 = sheet.createRow(3);
Cell cell30 = row3.createCell(0);
cell30.setCellValue("1000");
Cell cell31 = row3.createCell(1);
cell31.setCellValue(comparisons3);
workbook.write(out);
out.close();
System.out.println("Excel file written successfully.");
} catch (IOException e) {
e.printStackTrace();
}
}
}
```
In the above code, we create three different lists of sizes 10, 100, and 1000, and sort each of them using the MyArrayList class. We record the number of comparisons performed for each sort and print them to the console. We then create an Excel file and write the data to it, creating a graph with the data.
To create the graph in Excel, open the sorting.xlsx file and select the data in cells A1:B3. Click on the Insert tab and select the type of graph you want to create. You can then customize the graph as needed.
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