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公开(公告)号：US07191083B2
公开(公告)日：2007-03-13
申请号：US11490981
申请日：2006-07-20
IPC分类号： G01R35/00
CPC分类号： H03M13/6343 , G11B20/10009 , G11B20/10046 , G11B20/10055 , G11B20/10296 , G11B2220/2516 , H03M13/01 , H03M13/41 , H03M13/6505
摘要： Disclosed herein is an apparatus and method of calibrating the parameters of a Viterbi detector 138 in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. An offline algorithm for calculating the parameters of data-dependent noise predictive filters 304A-D is presented which has two phases: a noise statistics estimation or training phase, and a filter calculation phase. During the training phase, products of pairs of noise samples are accumulated in order to estimate the noise correlations. Further, the results of the training phase are used to estimate how wide (in bits) the noise correlation accumulation registers need to be. The taps [t2[k], t1[k], t0[k]] of each FIR filter are calculated based on estimates of the entries of a 3-by-3 conditional noise correlation matrix C[k] defined by Cij[k]=E(ni-3nj-3|NRZ condition k).
摘要翻译： 本文公开了一种校准维特比检测器138的参数的装置和方法，其中基于依赖于与分支对应的信号假设的噪声统计量来计算每个分支度量。 提出了一种用于计算数据相关噪声预测滤波器304A-D的参数的离线算法，其具有两个阶段：噪声统计估计或训练阶段和滤波器计算阶段。 在训练阶段，累积了噪声样本对的乘积，以估计噪声相关性。 此外，训练阶段的结果用于估计噪声相关累加寄存器的宽度（以比特为单位）。 抽头[t 2]，[0]，[0]，0＆lt; 1＆lt; 基于由C定义的3×3条件噪声相关矩阵C∈[k] 的条目的估计来计算每个FIR滤波器的SUB> [k] = E（n-i-3）n-3 / NRZ条件k）。
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公开(公告)号：US07165000B2
公开(公告)日：2007-01-16
申请号：US11109207
申请日：2005-04-18
IPC分类号： G06F19/00
CPC分类号： H03M13/6343 , G11B20/10009 , G11B20/10046 , G11B20/10055 , G11B20/10296 , G11B2220/2516 , H03M13/01 , H03M13/41 , H03M13/6505
摘要： Disclosed herein is an apparatus and method of calibrating the parameters of a Viterbi detector 138 in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. An offline algorithm for calculating the parameters of data-dependent noise predictive filters 304A–D is presented which has two phases: a noise statistics estimation or training phase, and a filter calculation phase. During the training phase, products of pairs of noise samples are accumulated in order to estimate the noise correlations. Further, the results of the training phase are used to estimate how wide (in bits) the noise correlation accumulation registers need to be. The taps [t2[k],t1[k],t0[k]] of each FIR filter are calculated based on estimates of the entries of a 3-by-3 conditional noise correlation matrix C[k] defined by Cij[k]=E(ni−3nj−3|NRZ condition k).
摘要翻译： 本文公开了一种校准维特比检测器138的参数的装置和方法，其中基于依赖于与分支对应的信号假设的噪声统计量来计算每个分支度量。 提出了一种用于计算数据相关噪声预测滤波器304A-D的参数的离线算法，其具有两个阶段：噪声统计估计或训练阶段和滤波器计算阶段。 在训练阶段，累积了噪声样本对的乘积，以估计噪声相关性。 此外，训练阶段的结果用于估计噪声相关累加寄存器的宽度（以比特为单位）。 抽头[t 2]，[0]，[0]，0＆lt; 1＆lt; 基于由C定义的3×3条件噪声相关矩阵C∈[k] 的条目的估计来计算每个FIR滤波器的SUB> [k] = E（n-i-3）n-3 / NRZ条件k）。
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公开(公告)号：US07522678B2
公开(公告)日：2009-04-21
申请号：US10402654
申请日：2003-03-28
IPC分类号： H03D1/00
CPC分类号： G11B20/10296 , G11B20/10009
摘要： An improved Viterbi detector is disclosed in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. Also disclosed is a method of reducing the complexity of the branch metric calculations by clustering branches corresponding to signals with similar signal-dependent noise statistics. A feature of this architecture is that the branch metrics are clustered into multiple groups, where all the members of each group draw input from a single, shared noise predictive filter corresponding to the group. In recording technologies as practiced today, physical imperfections in the representation of recorded user data in the recording medium itself are becoming the dominate source of noise in the read back data. This noise is highly dependent on what was (intended to be) written in the medium. The disclosed Viterbi detector exploits this statistical dependence of the noise on the signal.
摘要翻译： 公开了一种改进的维特比检测器，其中基于依赖于与分支对应的信号假设的噪声统计来计算每个分支度量。 还公开了一种通过对与具有相似的信号相关噪声统计信号的信号进行聚类的分支来降低分支度量计算的复杂度的方法。 该架构的一个特点是分支度量被聚集成多个组，其中每个组的所有成员从与组相对应的单个共享噪声预测滤波器中绘制输入。 在今天所采用的记录技术中，在记录介质本身中记录的用户数据的表示中的物理缺陷正在回读数据中成为主要的噪声源。 这种噪音很大程度上取决于介质中写的内容。 所公开的维特比检测器利用噪声对信号的统计依赖性。
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公开(公告)号：US06889154B2
公开(公告)日：2005-05-03
申请号：US10402033
申请日：2003-03-28
CPC分类号： H03M13/6343 , G11B20/10009 , G11B20/10046 , G11B20/10055 , G11B20/10296 , G11B2220/2516 , H03M13/01 , H03M13/41 , H03M13/6505
摘要： Disclosed herein is an apparatus and method of calibrating the parameters of a Viterbi detector 138 in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. An offline algorithm for calculating the parameters of data-dependent noise predictive filters 304A-D is presented which has two phases: a noise statistics estimation or training phase, and a filter calculation phase. During the training phase, products of pairs of noise samples are accumulated in order to estimate the noise correlations. Further, the results of the training phase are used to estimate how wide (in bits) the noise correlation accumulation registers need to be. The taps [t2[k], t1[k], t0[k]] of each FIR filter are calculated based on estimates of the entries of a 3-by-3 conditional noise correlation matrix C[k] defined by Cij[k]=E(ni−3nj−3|NRZ condition k).
摘要翻译： 本文公开了一种校准维特比检测器138的参数的装置和方法，其中基于依赖于与分支对应的信号假设的噪声统计量来计算每个分支度量。 提出了一种用于计算数据相关噪声预测滤波器304A-D的参数的离线算法，其具有两个阶段：噪声统计估计或训练阶段和滤波器计算阶段。 在训练阶段，累积了噪声样本对的乘积，以估计噪声相关性。 此外，训练阶段的结果用于估计噪声相关累加寄存器的宽度（以比特为单位）。 水龙头 2 > 1 [k] ， 0 基于由<？in-line-formula description = 3定义的3×3条件噪声相关矩阵C [k] 的条目的估计来计算每个FIR滤波器的 “In-line Formulas”end =“lead”？> C i> E E E E E =>>>>>>>>>>>>>>>>>>>>>>>>> j-3
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公开(公告)号：US07743314B2
公开(公告)日：2010-06-22
申请号：US11607492
申请日：2006-12-01
IPC分类号： H03M13/03
CPC分类号： G11B20/10296 , G11B20/10009
摘要： An improved Viterbi detector is disclosed in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. Also disclosed is a method of reducing the complexity of the branch metric calculations by clustering branches corresponding to signals with similar signal-dependent noise statistics. A feature of this architecture is that the branch metrics (and their corresponding square difference operators) are clustered into multiple groups, where all the members of each group draw input from a single, shared noise predictive filter corresponding to the group. In recording technologies as practiced today, physical imperfections in the representation of recorded user data in the recording medium itself are becoming the dominate source of noise in the read back data. This noise is highly dependent on what was (intended to be) written in the medium. The disclosed Viterbi detector exploits this statistical dependence of the noise on the signal.
摘要翻译： 公开了一种改进的维特比检测器，其中基于依赖于与分支对应的信号假设的噪声统计来计算每个分支度量。 还公开了一种通过对与具有相似的信号相关噪声统计信号的信号进行聚类的分支来降低分支度量计算的复杂度的方法。 该架构的一个特点是分支度量（及其对应的平方差运算符）被聚集成多个组，其中每个组的所有成员从与组相对应的单个共享噪声预测滤波器中绘制输入。 在今天所采用的记录技术中，在记录介质本身中记录的用户数据的表示中的物理缺陷正在回读数据中成为主要的噪声源。 这种噪音很大程度上取决于介质中写的内容。 所公开的维特比检测器利用噪声对信号的统计依赖性。
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公开(公告)号：US08015477B2
公开(公告)日：2011-09-06
申请号：US12819993
申请日：2010-06-21
IPC分类号： H03M13/03
CPC分类号： G11B20/10296 , G11B20/10009
摘要： An improved Viterbi detector is disclosed in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. Also disclosed is a method of reducing the complexity of the branch metric calculations by clustering branches corresponding to signals with similar signal-dependent noise statistics. A feature of this architecture is that the branch metrics (and their corresponding square difference operators) are clustered into multiple groups, where all the members of each group draw input from a single, shared noise predictive filter corresponding to the group. In recording technologies as practiced today, physical imperfections in the representation of recorded user data in the recording medium itself are becoming the dominate source of noise in the read back data. This noise is highly dependent on what was (intended to be) written in the medium. The disclosed Viterbi detector exploits this statistical dependence of the noise on the signal.
摘要翻译： 公开了一种改进的维特比检测器，其中基于依赖于与分支对应的信号假设的噪声统计来计算每个分支度量。 还公开了一种通过对与具有相似的信号相关噪声统计信号的信号进行聚类的分支来降低分支度量计算的复杂度的方法。 该架构的一个特点是分支度量（及其对应的平方差运算符）被聚集成多个组，其中每个组的所有成员从与组相对应的单个共享噪声预测滤波器中绘制输入。 在今天所采用的记录技术中，在记录介质本身中记录的用户数据的表示中的物理缺陷正在回读数据中成为主要的噪声源。 这种噪音很大程度上取决于介质中写的内容。 所公开的维特比检测器利用噪声对信号的统计依赖性。
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7.发明申请公开(公告)号：US20100322359A1
公开(公告)日：2010-12-23
申请号：US12819993
申请日：2010-06-21
IPC分类号： H04L27/06
CPC分类号： G11B20/10296 , G11B20/10009
摘要： An improved Viterbi detector is disclosed in which each branch metric is calculated based on noise statistics that depend on the signal hypothesis corresponding to the branch. Also disclosed is a method of reducing the complexity of the branch metric calculations by clustering branches corresponding to signals with similar signal-dependent noise statistics. A feature of this architecture is that the branch metrics (and their corresponding square difference operators) are clustered into multiple groups, where all the members of each group draw input from a single, shared noise predictive filter corresponding to the group. In recording technologies as practiced today, physical imperfections in the representation of recorded user data in the recording medium itself are becoming the dominate source of noise in the read back data. This noise is highly dependent on what was (intended to be) written in the medium. The disclosed Viterbi detector exploits this statistical dependence of the noise on the signal.
摘要翻译： 公开了一种改进的维特比检测器，其中基于依赖于与分支对应的信号假设的噪声统计来计算每个分支度量。 还公开了一种通过对与具有相似的信号相关噪声统计信号的信号进行聚类的分支来降低分支度量计算的复杂度的方法。 该架构的一个特点是分支度量（及其对应的平方差运算符）被聚集成多个组，其中每个组的所有成员从与组相对应的单个共享噪声预测滤波器中绘制输入。 在今天所采用的记录技术中，在记录介质本身中记录的用户数据的表示中的物理缺陷正在回读数据中成为主要的噪声源。 这种噪音很大程度上取决于介质中写的内容。 所公开的维特比检测器利用噪声对信号的统计依赖性。
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