This paper deals with the problem of speech enhancement when a corrupted speech signal with an additive colored noise is the only information available for processing. Kalman filtering is known as an effective speech enhancement technique, in which speech signal is usually modeled as autoregressive (AR) process and represented in the state-space domain.
标签： speech with enhancement corrupted
上传时间： 2015-09-07
上传用户：zhangyi99104144
This paper deals with the problem of speech enhancement when only a corrupted speech signal is available for processing. Kalman filtering is known as an effective speech enhancement technique, in which speech signal is usually modeled as autoregressive (AR) model and represented in the state-space domain.
标签： speech enhancement corrupted problem
上传时间： 2013-12-20
上传用户：569342831
ut 165 driver- driver corrupted
上传时间： 2013-12-19
上传用户：sxdtlqqjl
A user-space device driver can do many of the things that kernel drivers can t, such as perform a long-running computation, block while waiting for an event, or read files from the file system. Unlike kernel drivers, a user-space device driver can use other device drivers--that is, access the network, talk to a serial port, get interactive input from the user, pop up GUI windows, or read from disks. User-space drivers implemented using FUSD can be much easier to debug it is impossible for them to crash the machine, are easily traceable using tools such as gdb, and can be killed and restarted without rebooting even if they become corrupted. FUSD drivers don t have to be in C--Perl, Python, or any other language that knows how to read from and write to a file descriptor can work with FUSD. User-space drivers can be swapped out, whereas kernel drivers lock physical memory.
标签： user-space can drivers perform
上传时间： 2014-01-01
上传用户：saharawalker
卡耐基.梅隆大学的牛发写的关于孤立点和数据清洗的文章，全英文，2003年完成，Probabilistic Noise Identification and Data Cleaning，Real world data is never as perfect as we would like it to be and can often suffer from corruptions that may impact interpretations of the data, models created from the data, and decisions made based on the data. One approach to this problem is to identify and remove records that contain corruptions. Unfortunately, if only certain fields in a record have been corrupted then usable, uncorrupted data will be lost. In this paper we present LENS, an approach for identifying corrupted fields and using the remaining noncorrupted fields for subsequent modeling and analysis.
上传时间： 2017-08-29
上传用户：thinode
