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公开(公告)号：US08774968B2
公开(公告)日：2014-07-08
申请号：US13004517
申请日：2011-01-11
申请人： Chyon Hae Kim , Hiroshi Tsujino
发明人： Chyon Hae Kim , Hiroshi Tsujino
IPC分类号： G05B19/04
CPC分类号： B25J9/1666 , G05B2219/40446
摘要： A trajectory planning system obtains a trajectory for controlling a state of an object toward a goal state. The system includes a search tree generating section which registers a state of the object as a root of a search tree in a state space, registers a next state of the object after a lapse of a predetermined time interval obtained through dynamical relationships during the time interval as a branch of the search tree in the state space. The system further includes a known-state registration tree storing section which stores a known-state registration tree and a known-state registration tree generating section which determines a cell to which the next state belongs among a plurality of cells previously prepared by segmenting the state space, determines whether or not a state which belongs to the cell has already been registered as a branch of the known-state registration tree, discards the next state when a state which belongs to the cell has been registered, and registers the next step as a branch of the known-state registration tree when a state which belongs to the cell has not been registered. The system further includes a trajectory generating section which selects a state whose distance to the goal state is minimum among states registered as branches of the known-state registration tree and obtains a trajectory using a sequence of states in a backward direction from the state toward the root of the known-state registration tree.
摘要翻译： 轨迹规划系统获得用于控制物体朝向目标状态的状态的轨迹。 该系统包括搜索树生成部分，其将对象的状态作为搜索树的根登记在状态空间中，在经过在时间间隔期间通过动态关系获得的预定时间间隔之后登记对象的下一状态 作为状态空间中搜索树的分支。 该系统还包括已知状态注册树存储部分，其存储已知状态注册树和已知状态注册树生成部分，该已知状态注册树生成部分通过分割状态来确定先前准备的多个小区中下一状态所属的小区 空间，确定属于小区的状态是否已经被注册为已知状态注册树的分支，当属于小区的状态已被注册时，丢弃下一状态，并将下一步骤注册为 当属于小区的状态尚未被注册时，已知状态注册树的分支。 该系统还包括：轨迹生成部，其选择在已知状态登记树的分支中登记为状态的目标状态的距离为最小的状态，并使用从状态朝向状态的向后方向的状态序列获取轨迹 已知状态注册树的根。
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公开(公告)号：US08521678B2
公开(公告)日：2013-08-27
申请号：US12792853
申请日：2010-06-03
CPC分类号： G06N99/005
摘要： A learning control system according to the present invention is one which performs learning of action values of actions in an apparatus which identifies its state as one of predetermined states, and selects an action based on the obtained action values and the identified state. The learning control system includes n action value learning devices including the first to the n th learning devices which perform learning of n action values from Q1 to Qn, assuming that n is a positive integer and an action value determining device which determines the total action value of an action Q of each state based on outputs of the n action value learning devices. In the learning control system, the first target value of the first action value learning device is determined based on the reward r obtained after an action has been carried out by the next state and a total action value Q′ that was prepared for the action selection in the next state, and the first learning device updates the first action value Q1 using the first target value. When n is 2 or more, the n-th a target value of the n th action value learning device is set to the difference between the (n−1) th target value of the (n−1) th learning device and the action value Qn-1, and the n th learning device updates the n th action value Q1 using the n th target value.
摘要翻译： 根据本发明的学习控制系统是在将其状态识别为预定状态之一的装置中执行动作值的学习，并且基于获得的动作值和识别状态来选择动作。 该学习控制系统包括n个动作值学习装置，其包括从Q1到Qn执行n个动作值的学习的第一到第n个学习装置，假设n是正整数，动作值确定装置确定总动作值 基于n个动作值学习装置的输出的每个状态的动作Q。 在学习控制系统中，第一动作值学习装置的第一目标值基于在下一个状态下执行动作之后获得的奖励r和为动作选择准备的总动作值Q'来确定 并且第一学习装置使用第一目标值更新第一动作值Q1。 当n为2以上时，将第n动作值学习装置的第n个目标值设定为第（n-1）个学习装置的第（n-1）个目标值与动作 值Qn-1，并且第n学习装置使用第n个目标值来更新第n个动作值Q1。
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3.发明授权Sound source separation system which converges a separation matrix using a dynamic update amount based on a cost function 有权声源分离系统，其使用基于成本函数的动态更新量收敛分离矩阵公开(公告)号：US08131542B2
公开(公告)日：2012-03-06
申请号：US12133691
申请日：2008-06-05
CPC分类号： G06K9/6242 , G06K9/6245 , G10L21/028 , G10L2021/02166
摘要： A system capable of separating sound source signals with high precision while improving a convergence rate and convergence precision. A process of updating a current separation matrix Wk to a next separation matrix Wk+1 such that a next value J(Wk+1) of a cost function is closer to a minimum value J(W0) than a current value J(Wk) is iteratively performed. An update amount ΔWk of the separation matrix is increased as the current value J(Wk) of the cost function is increased and is decreased as a current gradient ∂J(Wk)/∂W of the cost function is rapid. On the basis of input signals x from a plurality of microphones Mi and an optimal separation matrix W0, it is possible to separate sound source signals y(=W0·x) with high precision while improving a convergence rate and convergence precision.
摘要翻译： 一种能够在提高收敛速度和收敛精度的同时高精度地分离声源信号的系统。 将当前分离矩阵Wk更新为下一个分离矩阵Wk + 1的过程，使得成本函数的下一个值J（Wk + 1）比当前值J（Wk）更接近最小值J（W0） 被迭代地执行。 随着成本函数的当前值J（Wk）增加，并且随着成本函数的当前梯度∂J（Wk）/∂W）快速地减小，分离矩阵的更新量＆Dgr; Wk增加。 基于来自多个麦克风Mi的输入信号x和最优分离矩阵W0，可以在提高收敛速度和收敛精度的同时高精度地分离声源信号y（= W0·x）。
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公开(公告)号：US20090018828A1
公开(公告)日：2009-01-15
申请号：US10579235
申请日：2004-11-12
申请人： Kazuhiro Nakadai , Hiroshi Tsujino , Hiroshi Okuno
发明人： Kazuhiro Nakadai , Hiroshi Tsujino , Hiroshi Okuno
IPC分类号： G10L19/14
CPC分类号： G10L15/20 , G10L21/028 , G10L2021/02166
摘要： An automatic speech recognition system includes: a sound source localization module for localizing a sound direction of a speaker based on the acoustic signals detected by the plurality of microphones; a sound source separation module for separating a speech signal of the speaker from the acoustic signals according to the sound direction; an acoustic model memory which stores direction-dependent acoustic models that are adjusted to a plurality of directions at intervals; an acoustic model composition module which composes an acoustic model adjusted to the sound direction, which is localized by the sound source localization module, based on the direction-dependent acoustic models, the acoustic model composition module storing the acoustic model in the acoustic model memory; and a speech recognition module which recognizes the features extracted by a feature extractor as character information using the acoustic model composed by the acoustic model composition module.
摘要翻译： 一种自动语音识别系统，包括：声源定位模块，用于基于由所述多个麦克风检测到的声信号来定位扬声器的声音方向; 声源分离模块，用于根据声音方向将扬声器的语音信号与声学信号分离; 声学模型存储器，其存储以间隔被调整到多个方向的方向相关的声学模型; 声学模型合成模块，其基于所述方向相关的声学模型，将声学模型组合模块存储在所述声学模型存储器中;声学模型组合模块，其将声学模型组合模块存储在所述声学模型存储器中; 以及语音识别模块，其使用由声学模型组合模块组成的声学模型识别由特征提取器提取的特征作为字符信息。
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公开(公告)号：US20080306739A1
公开(公告)日：2008-12-11
申请号：US12133691
申请日：2008-06-05
IPC分类号： G10L11/00
CPC分类号： G06K9/6242 , G06K9/6245 , G10L21/028 , G10L2021/02166
摘要： A system capable of separating sound source signals with high precision while improving a convergence rate and convergence precision. A process of updating a current separation matrix Wk to a next separation matrix Wk+1 such that a next value J(Wk+1) of a cost function is closer to a minimum value J(W0) than a current value J(Wk) is iteratively performed. An update amount ΔWk of the separation matrix is increased as the current value J(Wk) of the cost function is increased and is decreased as a current gradient ∂J(Wk)/∂W of the cost function is rapid. On the basis of input signals x from a plurality of microphones Mi and an optimal separation matrix W0, it is possible to separate sound source signals y(=W0·x) with high precision while improving a convergence rate and convergence precision.
摘要翻译： 一种能够在提高收敛速度和收敛精度的同时高精度地分离声源信号的系统。 将当前分离矩阵Wk更新为下一个分离矩阵Wk + 1的过程，使得成本函数的下一个值J（Wk + 1）比当前值J（Wk）更接近最小值J（W0） 被迭代地执行。 随着成本函数的当前值J（Wk）增加，并且随着成本函数的当前梯度∂J（Wk）/∂W）快速地减小，分离矩阵的更新量DeltaWk增加。 基于来自多个麦克风Mi和最佳分离矩阵W0的输入信号x，可以在提高收敛速度和收敛精度的同时高精度地分离声源信号y（= W0.x）。
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公开(公告)号：US20070183618A1
公开(公告)日：2007-08-09
申请号：US10588801
申请日：2005-02-10
CPC分类号： H04R3/12 , H04R1/323 , H04R27/00 , H04R2201/401 , H04R2217/03 , H04R2430/20
摘要： An ultra-directional speaker having a modulator 33 for modulating an ultrasonic carrier signal with an input electric signal from an audible sound signal source, and an emitter 44 for emitting an output of the modulator 33 is mounted in a moving object 1 having a target tracking system for sensing a target in a surrounding space in real time using the above-mentioned emitter 44. The moving object equipped with ultra-directional speaker can therefore transmit a voice only to a specific target through parametric action caused by the nonlinearity of finite amplitude of ultrasonic wave.
摘要翻译： 具有调制器33的超方向扬声器安装在具有目标跟踪的移动物体1中，调制器33用于从可听见的声音信号源输入电信号调制超声波载波信号，发射器44用于发射调制器33的输出。 系统，用于使用上述发射器44实时地感测周围空间中的目标。 因此，配备有超声波扬声器的移动物体可以通过由超声波的有限幅度的非线性引起的参数化动作将声音传输到特定目标。
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公开(公告)号：US06185337B2
公开(公告)日：2001-02-06
申请号：US08989416
申请日：1997-12-12
IPC分类号： G06K970
CPC分类号： G06K9/00221
摘要： In an artificial intelligence system for image recognition, a global image of an object is input from a camera or other optical pick-up device, and is processed in a global image processing means, which performs analytical processing on the global image by extracting global characteristics of the input image and evaluating consistency of the extracted global characteristics. Simultaneously, the image data is processed in a local image processing means which undertakes analytical processing on a plurality of local images defining local portions of the image to be recognized. The local image processing means is constructed by plural modules, each further defined by sub-modules, which conduct respective analyses corresponding to local images having characteristics useful in recognizing the global image, wherein each local processor extracts characteristics of an input local image and evaluates consistency of the extracted characteristic with the object to be recognized. Importantly, the global image processing means receives inputs from the local modules, and deactivates functions of local modules which are inconsistent with the global characteristics, while activating and promoting functions of local modules which are consistent with the global characteristics. Through top-down control from the global image processor, as well as inter-module signals between respective local processing modules, since inconsistent processes are quickly discovered,
摘要翻译： 在用于图像识别的人造智能系统中，从相机或其他光学拾取装置输入对象的全局图像，并在全局图像处理装置中进行处理，全局图像处理装置通过提取全局特征来对全局图像执行分析处理 的输入图像和评估提取的全局特征的一致性。 同时，在局部图像处理装置中对图像数据进行处理，该图像处理装置对定义要识别的图像的局部部分的多个局部图像进行分析处理。 本地图像处理装置由多个模块构成，每个模块进一步由子模块限定，子模块进行对应于具有用于识别全局图像的特征的局部图像的相应分析，其中每个本地处理器提取输入局部图像的特征并评估一致性 提取的特征与要识别的对象。 重要的是，全局图像处理装置接收来自本地模块的输入，并且激活与全局特性不一致的本地模块的功能，同时激活和促进与全局特性一致的本地模块的功能。 通过全局图像处理器的自顶向下控制以及各个本地处理模块之间的模块间信号，由于快速发现不一致的过程，
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公开(公告)号：US5675663A
公开(公告)日：1997-10-07
申请号：US619990
申请日：1996-03-21
CPC分类号： G06K9/00241
摘要： An artificial visual apparatus and method for image recognition having a simple adaptive scaling mechanism enables the definition of scale invariant visual icons in a processing area corresponding to the anterior inferotemporal cortex (AIT) in a one-step, value-based decision making process. Icon related activity states resulting from sensory filtering to a fourth stage KL filter corresponding to the V4 area are recognized independent of the scale and position of the item to be recognized within the maximum visual field. The AIT processing area controls the window of attention in the V4 area and confines further processing onto this selected spotlight. The invention presents a biologically plausible method for scale invariant mapping from the V4 stage filter to the AIT processor. Filtering based on principal component analysis (PCA), or Karhunen-Loeve (KL) filtering, yields image data of the item of interest in the V4 stage filter, such data then being supplied to the AIT processor by a scale-invariant mapping process which controls the number of inputs to the KL filters to achieve constant resolution independent of the scale of the item of interest in the maximum visual field. Thus, the problem of scale-invariant mapping is reduced to a simple adaptive thresholding by feedforward inhibition at the AIT processor.
摘要翻译： 具有简单的自适应缩放机制的图像识别的人造视觉设备和方法使得能够在一步的基于价值的决策过程中在对应于前颞下皮质（AIT）的处理区域中定义尺度不变视觉图标。 与感觉滤波相关的图形相关活动状态与对应于V4区域的第四级KL滤波器相关，独立于要在最大视野内识别的项目的比例和位置。 AIT处理区域控制V4区域的注意窗口，并将进一步处理限制在此选择的聚光灯上。 本发明提出了一种用于从V4级滤波器到AIT处理器的尺度不变映射的生物似然的方法。 基于主成分分析（PCA）或Karhunen-Loeve（KL）滤波的过滤产生V4阶段过滤器中感兴趣项目的图像数据，然后通过尺度不变映射过程将该数据提供给AIT处理器， 控制KL滤波器的输入数量，以实现独立于最大视野中感兴趣项目的比例的恒定分辨率。 因此，尺度不变映射的问题通过在AIT处理器处的前馈抑制被简化为简单的自适应阈值。
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公开(公告)号：US08416957B2
公开(公告)日：2013-04-09
申请号：US12631434
申请日：2009-12-04
IPC分类号： H04R29/00
CPC分类号： G01S5/16
摘要： In a sound source localization system using a light emitting device for visualizing sound information, including: a light emitting device (40) including a microphone for receiving sound from a sound source (1, 2) and a light emitting means for emitting light based on the sound from the microphone; a generating section for generating light emitting information for the light emitting device (40); and a sound source localization section (60) for determining a position of the sound source based on the light emitting information from the generating section.
摘要翻译： 在使用发光装置进行可视化声音信息的声源定位系统中，包括：包括用于从声源（1,2）接收声音的麦克风的发光装置（40）和基于 来自麦克风的声音; 用于产生发光装置（40）的发光信息的发生部分; 以及声源定位部分（60），用于基于来自发生部分的发光信息确定声源的位置。
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10.发明授权公开(公告)号：US08290883B2
公开(公告)日：2012-10-16
申请号：US12556872
申请日：2009-09-10
申请人： Johane Takeuchi , Hiroshi Tsujino
发明人： Johane Takeuchi , Hiroshi Tsujino
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： A learning system according to the present invention includes an event list database for storing a plurality of event lists, each of the event lists being a set including a series of state-action pairs which reaches a state-action pair immediately before earning a reward, an event list managing section for classifying state-action pairs into the plurality of event lists for storing, and a learning control section for updating expectation of reward of a state-action pair which is an element of each of the event lists.
摘要翻译： 根据本发明的学习系统包括用于存储多个事件列表的事件列表数据库，每个事件列表是包括在获得奖励之前到达状态 - 动作对的一系列状态 - 动作对的集合， 用于将状态对对分为用于存储的多个事件列表的事件列表管理部分，以及用于更新作为每个事件列表的元素的状态对的奖励的期望的学习控制部分。
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