<nav id="uoms8"></nav> this program deals with homomorphic analysis of speech. it was homework Assignment in digital speech processing course. speech is synthesized using homomorphic filter.
標簽： speech homomorphic Assignment analysis
上傳時間： 2013-12-23
上傳用戶：亞亞娟娟123
Linear Assignment Problem solver for Matlab
標簽： Assignment Problem Linear Matlab
上傳時間： 2014-01-11
上傳用戶：xiaodu1124
The target of the Assignment is to familiarize the student with MIMO channel modeling. The work is based on L. Schumacher’s MIMO channel model implementation, with added capacity analysis. First the channel model implementation is introduced, and thereafter analysis on MIMO channel with different parameters is done. Finally a short report on the results is written.
標簽： familiarize Assignment The the
上傳時間： 2014-01-01
上傳用戶：jjj0202
The task in this Assignment is to implement an airline routing system. Your system should be able to read in a ight network as a graph from a le, where airports are represented as vertices and ights between airports are represented as edges, take as input two airports and calculate the shortest route (ie path) between them.
標簽： system Assignment implement airline
上傳時間： 2017-09-07
上傳用戶：kiklkook
a non-sharing smart pointer class that can be used with STL containers such as std::map, vector, list, set, and deque. The smart pointer has an Assignment operator and greater than operator that call the target object s operator.
標簽： non-sharing containers pointer vector
上傳時間： 2015-06-15
上傳用戶：Late_Li
一種基于二維鏈表的稀疏矩陣模半板類設計 A template Class of sparse matrix. Key technology: bin,2-m linked matrix. constructors: 1.normal constuctor 2.copy constuctor. 3.Assignment constructor. Basic operator: 1. addition(sub) of two matrix 2. inverse of a matrix. 3. multiply of two matrix. etc.
標簽： matrix technology template linked
上傳時間： 2013-12-13
上傳用戶：lwwhust
SVMhmm: Learns a hidden Markov model from examples. Training examples (e.g. for part-of-speech tagging) specify the sequence of words along with the correct Assignment of tags (i.e. states). The goal is to predict the tag sequences for new sentences.
標簽： examples e.g. part-of-speech Training
上傳時間： 2015-12-05
上傳用戶：gyq
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each Assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new Assignments.
標簽： the decision clusters Cluster
上傳時間： 2013-12-21
上傳用戶：gxmm
This the OXO example code plus the presentation. It is intended to provide you with some clues about the structure and classes you may need for your second Assignment. I have also included the jar file.
標簽： presentation the intended example
上傳時間： 2016-06-20
上傳用戶：戀天使569
The acceptance and introduction of serial communication to more and more applications has led to requirements that the Assignment of message identifiers to communication functions be standardized for certain applications. These applications can be realized with CAN more comfortably, if the address range that originally has been defined by 11 identifier bits is enlarged
標簽： more communication introduction applications
上傳時間： 2014-01-04
上傳用戶：小草123
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