Matlab编程作业个人解决方案集锦

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资源摘要信息: "Personal Solutions to Programming Assignments on Matlab.zip" 该压缩包文件名为"Personal Solutions to Programming Assignments on Matlab.zip"，意味着它包含了针对特定编程作业的个人解决方案，这些解决方案是用Matlab编写的。Matlab是一种用于数值计算、可视化以及编程的高级技术计算语言和交互式环境，广泛应用于信号处理、图像处理、通信、控制系统、测试和测量等领域。此外，Matlab还提供了强大的工具箱，可以扩展其功能。 从标题来看，我们可以推断该压缩包主要包含以下几点重要知识点： 1. Matlab编程：文件中包含了个人为编程作业所编写的各种Matlab脚本和函数。这些作业可能是针对特定课程的，如“Coursera-Machine-Learning-Assignments-Personal-Solutions-master”文件夹所暗示的那样，这些作业可能与机器学习有关。因此，这里将涉及Matlab在机器学习领域的应用，包括数据预处理、模型建立、算法实现等方面。 2. 解决方案的个人化：提供的是个人解决方案，这表明文件中的代码是某个人根据自己的理解所写的。可能使用了不同的方法或算法来解决同样的问题，或者以不同的方式实现了课程要求的算法。这些内容可能包含了一些创新的思路或优化方法，对于想要理解问题不同解决角度的学习者来说，这是一个宝贵的资源。 3. Coursera课程配套材料：从文件名中包含“Coursera-Machine-Learning-Assignments-Personal-Solutions-master”这一点来看，这些解决方案可能是针对Coursera平台提供的机器学习课程的作业。Coursera是一个提供在线课程学习的平台，其中包含了来自世界各地顶尖大学和公司的课程。Matlab作为教学工具，经常在数据科学、机器学习等课程中被采用，因此，这个压缩包可能包含了一系列的作业文件，每一个都对应于课程中的特定任务。 4. 文件结构：文件中包含了一个“新建文件夹”，这个文件夹可能用于存储额外的资源，例如数据集、Matlab图形用户界面(GUI)文件、或额外的脚本和函数文件。新建文件夹的存在表明了文件组织结构的多样性，这可以帮助用户更好地管理和理解各个文件和项目之间的关系。 5. 编程实践和学习资源：这些个人解决方案的集合，不仅为学习者提供了一个参考的答案，而且可能还包含了详细的注释和说明，帮助理解Matlab代码的编写过程和思路。这对于学习Matlab编程、算法开发、以及掌握机器学习概念来说，是一个非常实用的资源。 从上述信息中我们可以得知，这个压缩包是一个涵盖了Matlab编程、机器学习应用和课程实践的资源集合。对于正在学习Matlab或者机器学习的学生和专业人士来说，这个压缩包提供了丰富的学习材料，能够帮助他们加深理解、扩展知识和提高编程技能。同时，它也是一个检验自己学习成果和进行代码比较的良好参照物。

Solutions to Programming Assignments （计算机网络教程:自顶向下方法 A.Forouzan）

2016-10-29 上传
计算机网络教程:自顶向下方法 佛罗赞 (Behrouz A.Forouzan) (作者) Solutions to Programming Assignments 程序作业的解答 都是java的代码

C.Programming.Step.By.Step.Beginners.To.Experts.Edition.B011EXMV7Q

2015-07-29 上传
Did you know many expert developers have started with learning C in order to become knowledgeable in computer programming? Were you aware that your children are learning C Programming today in their ...

kmeans++ matlab

2023-04-03 上传
Matlab has a built-in k-means function that can be used to perform clustering analysis on datasets. This function takes the dataset as input, along with the number of clusters to be formed, and ...

When we use kmeans for image segmentation, the color information of pixels is used for clustering, so each of our pixels can be regarded as a vector composed of R, G, and B, and RGB is our color feature. The specific process is similar to our example above, but the calculation object is changed from a scalar to a 3-dimensional vector. Please implement the kmean_color function in segmentation.py and call it to complete the segmentation of color images. (very similar to kmeans function)### Clustering Methods for colorful image def kmeans_color(features, k, num_iters=500): N=None # 像素个数 assignments = np.zeros(N, dtype=np.uint32) #Like the kmeans function above ### YOUR CODE HERE ### END YOUR CODE return assignments

2023-06-07 上传
segmented = assignments.reshape(img.shape[:2]) ``` In this example, we use `k=5` to cluster the pixel colors into 5 clusters. The resulting `segmented` image will have the same shape as the original ...

Assume you have four datasets: "employees", "departments", "projects", and "assignments". The scheme of these databases are as follows: The "employees" dataset contains employee information including a unique "employee_ID", "employee_name", and "department_ID". The "departments" dataset contains department information including a unique "department_ID" and "department_name". The "projects" dataset contains project information including a unique "project_ID", "project_name", and "department_ID". The "assignments" dataset contains information about which employees are assigned to which projects, including the "employee_ID" and "project_ID" associated with each assignment. Write a SQL query to retrieve the name and department of all employees who are assigned to a project that is not in the same department as their own department.

2023-06-07 上传
Here's a SQL query to retrieve the name and department of all employees who are assigned to a project that is not in the same department as their own department: ``` SELECT e.employee_name, d....

按照以下要求写出python代码，Suppose there are n assignments A= [a1, a2 …ai …an]that you need to complete before the deadline. An assignment ai= [durationi, deadlinei] need durationi days to complete and must be completed before or on deadlinei. You can only do one assignment at a time and start next assignment once the current assignment is completed. Assuming you start on day 1, implement an efficient algorithm to find the maximum number of assignments you can complete.

2023-03-14 上传
def max_assignments(A): # 按照deadlinei从小到大排序 A.sort(key=lambda x: x[1]) # 初始化当前时间和已完成的任务数 current_time = 0 completed = 0 for i in range(len(A)): # 如果当前时间加上任务需要...

write a short essay on the topic Trying to be a Good College Student

2023-03-31 上传
It is important to prioritize tasks and create a study schedule to ensure that all assignments are completed on time. Apart from academic performance, being a good college student also means being a...

The Sleeping Teaching Assistant A university computer science department has a teaching assistant (TA) who helps undergraduate students with their programming assignments during regular office hours. The TA’s office is rather small and has room for only one desk with a chair and computer. There are three chairs in the hallway outside the office where students can sit and wait if the TA is currently helping another student. When there are no students who need help during office hours, the TA sits at the desk and takes a nap. If a student arrives during office hours and finds the TA sleeping, the student must awaken the TA to ask for help. If a student arrives and finds the TA currently helping another student, the student sits on one of the chairs in the hallway and waits. If no chairs are available, the student will come back at a later time. Using POSIX threads, mutex locks, and/or semaphores, implement a solution that coordinates the activities of the TA and the students. Details for this assignment are provided below. Using Pthreads, begin by creating N students. Each will run as a separate thread. The TA will run as a separate thread as well. Student threads will alternate between programming for a period of time and seeking help from the TA. If the TA is available, they will obtain help. Otherwise, they will either sit in a chair in the hallway or, if no chairs are available, will resume programming and will seek help at a later time. If a student arrives and notices that the TA is sleeping, the student must notify the TA using a semaphore. When the TA finishes helping a student, the TA must check to see if there are students waiting for help in the hallway. If so, the TA must help each of these students in turn. If no students are present, the TA may return to napping. Perhaps the best option for simulating students programming—as well as the TA providing help to a student—is to have the appropriate threads sleep for a random period of time using the sleep() API:

2023-06-04 上传
This is a programming assignment that requires the use of POSIX threads, mutex locks, and/or semaphores to coordinate the activities of the TA and the students. Here is one possible solution: 1. ...

def get_y_preds(y_true, cluster_assignments, n_clusters): """ Computes the predicted labels, where label assignments now correspond to the actual labels in y_true (as estimated by Munkres) cluster_assignments: array of labels, outputted by kmeans y_true: true labels n_clusters: number of clusters in the dataset returns: a tuple containing the accuracy and confusion matrix, in that order """ confusion_matrix = metrics.confusion_matrix(y_true, cluster_assignments, labels=None) # compute accuracy based on optimal 1:1 assignment of clusters to labels cost_matrix = calculate_cost_matrix(confusion_matrix, n_clusters) indices = Munkres().compute(cost_matrix) kmeans_to_true_cluster_labels = get_cluster_labels_from_indices(indices) if np.min(cluster_assignments) != 0: cluster_assignments = cluster_assignments - np.min(cluster_assignments) y_pred = kmeans_to_true_cluster_labels[cluster_assignments] return y_pred

2023-07-16 上传
6. 根据聚类结果映射到真实标签的聚类标签数组 `kmeans_to_true_cluster_labels` 和聚类结果数组 `cluster_assignments`，计算预测标签数组 `y_pred`。 7. 返回预测标签数组 `y_pred`。 函数还计算了准确率和混淆...

all any sql

2023-05-03 上传
INNER JOIN project_assignments ON employees.employee_id = project_assignments.employee_id WHERE project_assignments.project_id = ANY ( SELECT project_id FROM projects WHERE budget > 1000000 ); ```
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