公开(公告)号：US08665270B2

公开(公告)日：2014-03-04

申请号：US12969673

申请日：2010-12-16

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06T15/40

CPC分类号： G06F17/10

摘要： A method of determining implicit hidden features of phenomena, representable by a point distribution in a space, includes the following steps: defining a set of first parameters describing effects of a phenomenon such as an event or process; defining a n-dimensional space, wherein the first parameters are represented by entity points; determining, as a function of measured values of the first parameters, additional geometrical points in the n-dimensional space, which are expected to provide additional characteristic parameters describing the phenomenon or additional locations where the phenomenon will produce its effects; adding the additional parameters or points, in recurrent sequence, to the first parameters or points, to define at each iterative step a shorter minimum spanning tree than at the preceding step; and displaying or printing the n-dimensional space, wherein the additional characteristic parameters or points are shown together with the first parameters and the geometrical point.

摘要翻译： 确定由空间中的点分布表示的现象的隐式隐藏特征的方法包括以下步骤：定义描述诸如事件或过程的现象的影响的一组第一参数; 定义n维空间，其中所述第一参数由实体点表示; 确定作为第一参数的测量值的函数的n维空间中的附加几何点，其预期将提供描述该现象的附加特征参数或该现象将产生其影响的附加位置; 将以循环序列的附加参数或点添加到第一参数或点，以在每个迭代步骤中定义比在前一步骤更短的最小生成树; 以及显示或打印n维空间，其中附加特征参数或点与第一参数和几何点一起示出。

公开(公告)号：US08326047B2

公开(公告)日：2012-12-04

申请号：US12664210

申请日：2008-07-02

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06K9/56

CPC分类号： G06T5/003 ,  G06T7/13 ,  G06T2207/20084

摘要： Image processing method that includes the steps of considering each image point as a node of an artificial neural network, and of processing the image as function of values of the nodes and of connections of each image point undergoing processing with neighboring image points, the image points of the processed image being obtained by iterative evolution steps of parameters defining the appearance as evolution steps of the value of nodes or by iterative evolution steps of values of the set of connections or by a combination of the evolutions, wherein the processing occurs by evolution iterative steps that are functions of connections of neighboring image points with the image point under examination, each of the neighboring image points being further considered as neighboring one or more or all adjacent image points, the functions providing immediate feedback contributions for determining appearance values of all other image points.

摘要翻译： 图像处理方法包括以下步骤：将每个图像点视为人造神经网络的节点，并且处理该图像作为节点数值的函数以及与相邻图像点进行处理的每个图像点的连接，图像点 通过将外观的定义作为节点值的演化步骤的参数的迭代演化步骤或连接组的迭代演化步骤或通过演化的组合来进行处理的图像的获取，其中处理通过进化迭代 作为相邻图像点与被检查图像点的连接的功能的步骤，每个相邻图像点进一步被认为是相邻的一个或多个或所有相邻图像点，所述功能提供用于确定所有其他的外观值的即时反馈贡献 图像点。

公开(公告)号：US20120155715A1

公开(公告)日：2012-06-21

申请号：US12969620

申请日：2010-12-16

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06K9/46 ,  G06K9/00

CPC分类号： G06F17/18

摘要： A method of determining features of events or processes having a dynamic evolution in space and/or time using measurements of parameters that calculate the most probable consequences of the event or process at a certain time includes: defining a set of measurable parameters describing the effects of the event or process, characteristic of the event or process, and measurable at a certain time; defining a n-dimensional space where the parameters describing the event or process are represented by entity points; determining, as a function of the measured values of the characteristic parameters describing the event or process at the certain time, a geometrical point in the n-dimensional space forces accumulate that are generated by the evolution of the event of process in time; and displaying or printing the n-dimensional space where the characteristic parameters are shown as entity points and as a geometrical point.

摘要翻译： 使用在某一时间计算事件或过程的最可能后果的参数的测量来确定具有空间和/或时间的动态演变的事件或过程的特征的方法包括：定义一组可测量的参数， 事件或过程，事件或过程的特征，并在一定时间可测量; 定义一个n维空间，其中描述事件或过程的参数由实体点表示; 根据在特定时间描述事件或过程的特征参数的测量值来确定由时间过程的演变产生的n维空间力中的几何积分; 并且显示或打印特征参数被显示为实体点的n维空间和几何点。

公开(公告)号：US08666707B2

公开(公告)日：2014-03-04

申请号：US12969887

申请日：2010-12-16

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06F7/60 ,  G06F17/10 ,  G06F17/50

CPC分类号： G06F17/5018 ,  G05B17/02 ,  G06F17/10 ,  G06N3/006

摘要： A model simulating the evolutionary dynamics of events or processes includes a non-linear adaptive mathematical system simulating spatial and temporal dynamics by using measured values of parameters describing the evolutionary condition of an event or process at different times. The model enables the definition of a n-dimensional array of points in a n-dimensional reference system having an axis that represents the values of the parameters being measured. The displacements of each of the points are computed as a function of their displacements in the array of points between a first time a second time and as a function of the distance of each of the points of the array from each of the points representing the measured parameters. The evolution of the event and or the model in time is visualized by displaying the points of the array of points at different times.

摘要翻译： 模拟事件或过程的进化动力学的模型包括通过使用描述不同时间的事件或过程的进化条件的参数的测量值来模拟空间和时间动力学的非线性自适应数学系统。 该模型使得能够在具有表示正被测量的参数的值的轴的n维参考系统中定义n维阵列。 每个点的位移被计算为它们在第二时间之间的点阵列中的位移的函数，并且作为阵列中的每个点的距离与表示所测量的每个点的距离的函数 参数。 通过在不同时间显示点阵列的点，可视化事件和模型在时间上的演变。

公开(公告)号：US08521668B2

公开(公告)日：2013-08-27

申请号：US13070854

申请日：2011-03-24

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06N3/00 ,  G06F17/10

CPC分类号： G06N3/02 ,  G06K9/00496

摘要： A method of reconstructing a causation process from time varying data describing an event, the data consisting in a certain number of entities each having a position in a space, and each of the entities being characterized by at least a quantity or value relatively to at least one feature and in the quantity or value relatively to at least one of the features of the entities at least at two different times or at each time instant of a sequence of time instants; the method describing the higher likelihood transition of all entities i, j from the time n to the time n+1 as a function of the position coordinate of the entity I and of the entity j and the quantity of the at least one feature of the entity I and of the entity j at the time n and at the time n+1: Mi,j[n,n+1]=ψ(xi,yi,qi[n],qi[n+1],xj,yj,qj[n],qj[n+1]). the function determining the strength of the connection between each entity i at time n and each other entity j at time n+1; the method determining the source causing changes in quantity of the entity j from the time n to the time n+1 as the entity i for which the strength of connection is a maximum. The invention relates also to a method of predicting the evolution dynamics of an event or process starting from the information about the causation process obtained from the above function.

摘要翻译： 一种从描述事件的时变数据重构因果过程的方法，所述数据由在一个空间中具有位置的一定数量的实体组成，并且每个实体的特征在于至少相对于至少一个数量或值 至少在一系列时刻的至少两个不同时间或每个时刻的实体的至少一个特征的一个特征和数量或数值; 描述作为实体I和实体j的位置坐标的函数的所有实体i，j从时间n到时间n + 1的较高似然转换的方法以及实体j的至少一个特征的量 实体I和实体j在时间n和时间n + 1：Mi，j [n，n + 1] = psi（xi，yi，qi [n]，qi [n + 1]，xj， yj，qj [n]，qj [n + 1]）。 确定时间n处的每个实体i与时间n + 1处的每个实体j之间的连接的强度的函数; 该方法确定源自实体j从时间n到时间n + 1的量的变化的源作为连接强度最大的实体i。 本发明还涉及从从上述功能获得的关于因果过程的信息开始的事件或过程的进化动态的预测方法。

公开(公告)号：US20100135574A1

公开(公告)日：2010-06-03

申请号：US12664210

申请日：2008-07-02

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06K9/62

CPC分类号： G06T5/003 ,  G06T7/13 ,  G06T2207/20084

摘要： Image processing method wherein each image is composed of an array of image points, so called pixels or voxels particularly in a two-, three-, or more dimensional space respectively each image point being univocally defined by its position within the array of image points and by one or more numerical parameters defining the image point appearance as regards characteristics of brightness, grey, colour shade or the like, and wherein each image point is considered to be a node of an artificial neural network, the image being processed as a function of parameters defining the appearance of each pixel as values of the nodes of said artificial neural network and as a function of connections of each pixel under processing with neighbouring pixels composed of pixels of a predetermined subset of pixels, particularly with neighbouring pixels of said pixel under processing, so called pixel window, while pixels of the new image i.e. of the processed image are obtained by iterative evolution steps of parameters defining the appearance such as evolution steps of the value of nodes or by iterative evolution steps of values of the set of connections or by a combination of said evolutions, wherein the processing occurs by evolution iterative steps where each step is a function also of connections of neighbouring pixels with the pixel under examination, when each of said neighbouring pixels of the pixel under examination is considered also as a neighbouring pixel of one ore more or all pixels adjacent to said neighbouring pixel, which function is an immediate feedback contribution for determining appearance values of all other pixels.

摘要翻译： 图像处理方法，其中每个图像由图像点阵列组成，所谓的像素或体素，特别是在二维，三维或更多维空间中，每个图像点由其在图像点阵列内的位置单一地定义， 通过限定关于亮度，灰度，色彩等的特征的图像点外观的一个或多个数值参数，并且其中每个图像点被认为是人造神经网络的节点，该图像被作为 将每个像素的外观定义为所述人造神经网络的节点的值的参数，以及作为处理中的每个像素的连接的函数的函数，所述相邻像素由预定子像素的像素组成的相邻像素，特别是与处理中的所述像素的相邻像素 ，所谓的像素窗口，而通过迭代演化步骤获得经处理的图像的新图像的像素 定义外观的参数，例如节点值的演进步骤或连接组的值的迭代演进步骤或所述演化的组合，其中处理通过进化迭代步骤进行，其中每个步骤也是 当被检查像素的所述相邻像素的每一个也被认为是与所述相邻像素相邻的一个或多个像素的相邻像素时，相邻像素与被检查像素的连接，该函数是用于确定的即时反馈贡献 所有其他像素的外观值。

公开(公告)号：US07672517B2

公开(公告)日：2010-03-02

申请号：US10516879

申请日：2003-03-10

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06K9/36

CPC分类号： G06T5/20 ,  G06T7/0012

摘要： A method for encoding pixels of digital or digitized images, i.e., images consisting of a set of image dots, named pixels in two-dimensional images and voxels in three-dimensional images, each of said pixels or voxels being represented by a set of values which correspond to a visual aspect of the pixel on a display screen or in a printed image. According to the invention, the pixels or voxels of at least one portion of interest of the digital or digitized image or each pixel or voxel of the set of pixels or voxels which form the image is uniquely identified with a vector whose components are given by the date of the pixels or voxels to be encoded and by the data of at least one or at least some or of all of the pixels around the pixels to be encoded and arranged within a predetermined subset of pixels or voxels included in the whole set of pixels or voxels which form the image.

摘要翻译： 用于编码数字或数字化图像的像素的方法，即由一组图像点组成的图像，二维图像中的命名像素和三维图像中的体素，每个所述像素或体素由一组值表示 其对应于显示屏幕上或打印图像中的像素的视觉方面。 根据本发明，数字或数字化图像的感兴趣的至少一部分的像素或体素或形成图像的像素或体元组的每个像素或体素被唯一地识别，其矢量由 要编码的像素或体素的日期以及待编码和排列在包含在整个像素集合中的像素或体素的预定子集内的像素周围的至少一个或至少一个或全部像素的数据 或形成图像的体素。

公开(公告)号：US08665269B2

公开(公告)日：2014-03-04

申请号：US12969620

申请日：2010-12-16

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06T15/40

CPC分类号： G06F17/18

摘要： A method of determining features of events or processes having a dynamic evolution in space and/or time using measurements of parameters that calculate the most probable consequences of the event or process at a certain time includes: defining a set of measurable parameters describing the effects of the event or process, characteristic of the event or process, and measurable at a certain time; defining a n-dimensional space where the parameters describing the event or process are represented by entity points; determining, as a function of the measured values of the characteristic parameters describing the event or process at the certain time, a geometrical point in the n-dimensional space forces accumulate that are generated by the evolution of the event of process in time; and displaying or printing the n-dimensional space where the characteristic parameters are shown as entity points and as a geometrical point.

摘要翻译： 使用在某一时间计算事件或过程的最可能后果的参数的测量来确定具有空间和/或时间的动态演变的事件或过程的特征的方法包括：定义一组可测量的参数， 事件或过程，事件或过程的特征，并在一定时间可测量; 定义一个n维空间，其中描述事件或过程的参数由实体点表示; 根据在特定时间描述事件或过程的特征参数的测量值来确定由时间过程的演变产生的n维空间力中的几何积分; 并且显示或打印特征参数被显示为实体点的n维空间和几何点。

公开(公告)号：US20120246101A1

公开(公告)日：2012-09-27

申请号：US13070854

申请日：2011-03-24

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06N3/00 ,  G06F17/10

CPC分类号： G06N3/02 ,  G06K9/00496

摘要： A method of reconstructing a causation process from time varying data describing an event, the data consisting in a certain number of entities each having a position in a space, and each of the entities being characterized by at least a quantity or value relatively to at least one feature and in the quantity or value relatively to at least one of the features of the entities at least at two different times or at each time instant of a sequence of time instants; the method describing the higher likelihood transition of all entities i, j from the time n to the time n+1 as a function of the position coordinate of the entity I and of the entity j and the quantity of the at least one feature of the entity I and of the entity j at the time n and at the time n+1: Mi,j[n,n+1]=ψ(xi, yi, qi[n], qi[n+1], xj, yj, qj[n], qj[n+1]). the function determining the strength of the connection between each entity i at time n and each other entity j at time n+1; the method determining the source causing changes in quantity of the entity j from the time n to the time n+1 as the entity i for which the strength of connection is a maximum. The invention relates also to a method of predicting the evolution dynamics of an event or process starting from the information about the causation process obtained from the above function.

摘要翻译： 一种从描述事件的时变数据重构因果过程的方法，所述数据由在一个空间中具有位置的一定数量的实体组成，并且每个实体的特征在于至少相对于至少一个数量或值 至少在一系列时刻的至少两个不同时间或每个时刻的实体的至少一个特征的一个特征和数量或数值; 描述作为实体I和实体j的位置坐标的函数的所有实体i，j从时间n到时间n + 1的较高似然转换的方法以及实体j的至少一个特征的量 实体I和实体j在时间n和时间n + 1：Mi，j [n，n + 1] =ψ（xi，yi，qi [n]，qi [n + 1]，xj， yj，qj [n]，qj [n + 1]）。 确定时间n处的每个实体i与时间n + 1处的每个实体j之间的连接的强度的函数; 该方法确定源自实体j从时间n到时间n + 1的量的变化的源作为连接强度最大的实体i。 本发明还涉及从从上述功能获得的关于因果过程的信息开始的事件或过程的进化动态的预测方法。

公开(公告)号：US20120158373A1

公开(公告)日：2012-06-21

申请号：US12969887

申请日：2010-12-16

申请人： Paolo Massimo Buscema

发明人： Paolo Massimo Buscema

IPC分类号： G06F17/10

CPC分类号： G06F17/5018 ,  G05B17/02 ,  G06F17/10 ,  G06N3/006

摘要： A model simulating the evolutionary dynamics of events or processes includes a non linear adaptive mathematical system simulating the spatial and temporal dynamics of the event or processes by using measured values of a certain number of parameters describing the evolutionary condition of the event or process at certain different times. The values of such parameters are measured at a first time and at least a second time different from and following the first time. The model enables the definition of a n-dimensional array of points in a n-dimensional reference system having an axis that represents the values of the parameters being measured, the parameters in the array being represented by special points in the array of points. The displacements of each of the points of the array of points are computed as a function of the displacements in the array of points of each of the points representing the measured parameter values between a first time of measurement and at least a successive second time of measurement and as a function of the distance of each of the points of the array of points from each of the points representing the measured parameters. The evolution of the event and or the model in time is visualized by displaying the points of the array of points at different times.

摘要翻译： 模拟事件或过程的进化动力学的模型包括通过使用描述事件或过程在某些不同的进化条件的一定数量参数的测量值来模拟事件或过程的空间和时间动力学的非线性自适应数学系统 次 这些参数的值在第一时间和至少第二时间不同于第一次之后被测量。 该模型能够定义n维参考系统中的点的n维阵列，其具有表示正被测量的参数的值的轴，阵列中的参数由点阵列中的特殊点表示。 计算点阵列中的每个点的位移作为表示在第一测量时间和至少连续的第二次测量时间之间的测量参数值的每个点的点阵列中的位移的函数的函数 并且作为来自表示测量参数的每个点的点阵列中的每个点的距离的函数。 通过在不同时间显示点阵列的点，可视化事件和模型在时间上的演变。