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对比文件列表
2009-03-19_发明申请_US20090077404A1 Method and system of reducing power consumption of system on chip based on analog-to-digital control circuitry_+++D_e_f_i_j+++.docx
2026-03-10 19:04
2010-08-26_发明申请_US20100214216A1 MOTION SENSING AND PROCESSING ON MOBILE DEVICES_+++A_B_C_G_H_d_e_f_j+++.docx
2026-03-10 19:04
2011-05-10_发明授权_US07941682B2 Optimum power management of system on chip based on tiered states of operation_+++a_d_e_f_i_j+++.docx
2026-03-10 19:04
2012-03-29_发明专利_JP2012507802A Control and access of content to use the motion processing on mobile devices_+++A_B_C_G_H_d_e_f+++.docx
2026-03-10 19:04
2012-10-04_发明申请_US20120254878A1 MECHANISM FOR OUTSOURCING CONTEXT-AWARE APPLICATION-RELATED FUNCTIONALITIES TO A SENSOR HUB_+++A_D_c_f_g_j+++.docx
2026-03-10 19:04
2013-01-23_发明公开_CN102893257A 将上下文感知应用相关功能性外派给传感器集线器的机制_+++A_D_E_F_G_I_c+++.docx
2026-03-10 19:04
2013-04-25_发明申请_US20130103212A1 METHOD AND APPARATUS FOR PROVIDING CONTEXT-BASED POWER CONSUMPTION CONTROL_+++C_G_a_b_d_f_h+++.docx
2026-03-10 19:04
2013-09-12_发明申请_US20130238921A1 SYSTEMS AND METHODS FOR LOW POWER PROCESSING BASED ON LOCATION INFORMATION_+++B_C_D_G_H_a_f+++.docx
2026-03-10 19:04
2014-11-27_发明申请_US20140351560A1 Low Power Management of Multiple Sensor Integrated Chip Architecture_+++D_a_c_e_f_g_i_j+++.docx
2026-03-10 19:04
WO2010056548A1_Description_20260304_2053_+++A_B_C_D_H_e_f_g+++.docx
2026-03-10 19:04
WO2012134546A1_Description_20260304_2053_+++A_C_D_G_b_e_f_h+++.docx
2026-03-10 19:04
WO2014100546A1_Description_20260304_2053_+++D_e_f_i+++.docx
2026-03-10 19:04
2010-08-26_发明申请_US20100214216A1 MOTION SENSING AND PROCESSING ON MOBILE DEVICES_+++A_B_C_G_H_d_e_f_j+++.docx

**对比文件名称**:2010-08-26_发明申请_US20100214216A1 MOTION SENSING AND PROCESSING ON MOBILE DEVICES

**目标专利名称**:用于传感器数据的超低电力处理的算法引擎 CN106716298B

**本次调用模型名称**:GPT-4

## 特征比对表格

技术特征描述及公开性判断结果对比文件原文引用公开性论述
**技术特征A:其包括:由通用处理器配置传感器融合引擎,《直接公开》**[0055] “...application processor 12 can implement the gesture processing and recognition described herein based on sensor inputs from a motion processing unit (MPU™) 20... an API layer can be implemented in layer 13 of processor 12 which allows communication of the states of application programs running on the processor to the MPU 20 as well as API commands (e.g., over bus 21), allowing the MPU 20 to implement some or all of the gesture processing and recognition...”对比文件公开了应用处理器(Application Processor 12)可以通过API命令配置运动处理单元(MPU 20)。应用处理器作为通用计算核心,其功能等同于目标专利中的“通用处理器”。MPU 20集成了运动传感器和硬件处理单元,用于处理传感器数据,其功能对应于目标专利中的“传感器融合引擎”。因此,本领域技术人员能够毫无疑义地得出,通用处理器(应用处理器)配置传感器融合引擎(MPU)的技术方案已被直接公开。
**技术特征B:所述传感器融合引擎包括用于执行多个传感器数据处理算法中的每一者的专用硬件电路,《直接公开》**[0060] “In some embodiments, the MPU 20 can also include a hardware processor or processing block 30. Hardware processing block 30 can include logic, microprocessors, or controllers to provide processing of motion sensor data in hardware. For example, motion algorithms, or parts of algorithms, may be implemented by block 30 in some embodiments...”对比文件明确公开了MPU 20包含硬件处理块30,该块包含逻辑、微处理器或控制器,用于以硬件方式处理运动传感器数据,并可实现运动算法。该硬件处理块是执行特定传感器数据处理算法的专用硬件电路,与目标专利中“用于执行多个传感器数据处理算法中的每一者的专用硬件电路”作用相同。因此,该技术特征被直接公开。
**技术特征C:其中所述多个传感器数据处理算法包括用于从多个传感器融合传感器数据的算法《直接公开》**[0060] “Some embodiments can provide a sensor fusion algorithm that is implemented by the hardware processing block 30 to process all the axes of motion of provided sensors to determine the movement of the handheld electronic device in space including the sensor data provided by both accelerometers and gyroscopes of the device 10.” <br> [0069] “In one implementation, in which gyroscopes and accelerometers are used, the gyroscope and accelerometer data may be fused to provide a better orientation sensor... In one implementation, the gyroscope and accelerometer data may be fused to provide a 3 degree-of-freedom orientation sensor using, e.g., a Kalman filter or a complementary filter.”对比文件多次提及并详细描述了“传感器融合算法”(sensor fusion algorithm),该算法用于处理来自多个传感器(如陀螺仪和加速度计)的数据,以确定设备的运动。这直接对应于目标专利中“用于从多个传感器融合传感器数据的算法”。因此,该技术特征被直接公开。
**技术特征D:根据所述配置,将所述通用处理器置于低电力睡眠模式中《隐含公开》**[0194] “The motion sensors in the device may also be used to control the power management of the system. For example, if it is determined from the motion sensors that the device has been stationary for a long time... then the device may enter a lower power state such as a sleep mode.” <br> [0195] “... the motion sensors may be powered down to conserve power. Pressing the button may cause the sensors to power up before motion sensing begins.”对比文件公开了设备可以根据运动传感器信息进入低功耗睡眠模式,以及为了省电可以关闭传感器。虽然未明确描述“根据配置,将通用处理器置于低电力睡眠模式中”这一具体时序,但本领域技术人员结合对比文件公开的电力管理动机([0194])以及应用处理器配置MPU后可能无需持续工作的上下文,能够合理推断出:为了进一步节省电力,在完成对MPU(传感器融合引擎)等组件的配置后,通用处理器可以进入低电力睡眠模式。这是一种合理的、符合系统设计逻辑的隐含公开。
**技术特征E:响应于来自多个传感器中的至少一者的中断,唤醒外围控制器《隐含公开》**[0195] “Pressing the button may cause the sensors to power up before motion sensing begins... For example, when the button is not depressed, the gyroscopes may alternate between being off for 1 second and on for 0.1 seconds. When the button is depressed, the gyroscope may be turned on to full power...”对比文件描述了通过按钮(一种外部触发信号)来唤醒或上电传感器系统。虽然未明确描述来自传感器本身的数据就绪中断,但本领域技术人员知晓,在传感器系统中,传感器产生中断信号通知控制器数据就绪是常见技术手段。结合对比文件公开的“响应外部触发(按钮)来唤醒/激活传感系统”这一原理,可以合理推断出,系统也可以设计为“响应来自传感器的中断来唤醒负责数据采集的外围控制器”。因此,该技术特征被隐含公开。
**技术特征F:在唤醒之后,当所述通用处理器处于所述低电力睡眠模式中时,以所述外围控制器读取所述多个传感器中的每一者所产生的数据且将所述数据存储到伴随存储器中《隐含公开》**[0066] “...The MPU samples motion sensor data at a higher rate and record the sensor data to a hardware buffer... The application processor 12 reads all sensor data accumulated in the hardware buffer since the last time it read the buffer...” <br> [0060] “Some embodiments can include a hardware buffer in the block 30 to store sensor data received from the gyroscopes 26 and accelerometers 28.”对比文件公开了MPU可以以高频率采样传感器数据并将其记录(存储)到硬件缓冲区(hardware buffer)中,而应用处理器则以较低频率读取该缓冲区。MPU在此承担了数据采集和缓冲的功能。虽然对比文件未明确说明此时应用处理器处于睡眠模式,但结合特征D的隐含公开(处理器可睡眠)以及MPU独立进行数据采集和缓冲的教导,本领域技术人员能够合理推断出:当应用处理器(通用处理器)处于低电力睡眠模式时,MPU(其集成了传感器接口和处理功能,可视为执行了“外围控制器”的数据读取和“伴随存储器”的缓冲功能)可以独立地读取传感器数据并存储到其硬件缓冲区中。因此,该技术特征被隐含公开。
**技术特征G:以及以所述传感器融合引擎处理存储在所述伴随存储器中的所述数据,《直接公开》**[0060] “Hardware processing block 30 can include logic, microprocessors, or controllers to provide processing of motion sensor data in hardware.” <br> [0066] “...The motion algorithms are then updated in quick succession based on the retrieved multiple sensor data points...”对比文件明确公开了硬件处理块30(属于MPU,即传感器融合引擎)对运动传感器数据进行处理。这些数据可以来自其内部的硬件缓冲区(即隐含公开的“伴随存储器”)。因此,“以传感器融合引擎处理存储的数据”这一技术特征被直接公开。
**技术特征H:其中所述配置包括配置所述传感器融合引擎以使用用于执行所述融合算法的所述专用硬件电路来执行所述处理。《直接公开》**[0055] “...an API layer can be implemented in layer 13 of processor 12 which allows communication of the states of application programs running on the processor to the MPU 20 as well as API commands (e.g., over bus 21), allowing the MPU 20 to implement some or all of the gesture processing and recognition...” <br> [0060] “Some embodiments can provide a sensor fusion algorithm that is implemented by the hardware processing block 30...”对比文件公开了应用处理器通过API命令配置MPU,以及MPU中的硬件处理块30用于实现传感器融合算法。这直接对应于目标专利中“配置传感器融合引擎以使用专用硬件电路来执行处理(包括融合算法)”。因此,该技术特征被直接公开。
**技术特征I:其中唤醒所述外围控制器是通过始终接通子系统AOSS来执行。《未公开》**(对比文件全文中未提及“始终接通子系统(AOSS)”或功能完全相同的模块。)目标专利中的“始终接通子系统(AOSS)”是一个特定模块,负责在系统其他部分休眠时维持供电、接收传感器中断并唤醒外围控制器等。对比文件中不存在具有相同功能和名称的子系统。虽然对比文件提到了电力管理([0194])和通过按钮唤醒([0195]),但这与由专用、始终接通的AOSS来执行唤醒有本质区别。本领域技术人员无法从对比文件中直接或隐含地得出该技术特征。
**技术特征J:其中所述通用处理器、所述传感器融合引擎、所述伴随存储器以及所述外围控制器位于芯片上系统SoC的低电力岛状物内。《隐含公开》**[0092] “In one implementation, the MPU can measure at least two axes of rotation and at least one axis of acceleration, in which components of the device are integrated in a single package, e.g., through wafer-scale integration.” <br> (涉及系统集成和封装)对比文件强调了MPU(传感器融合引擎)及其相关传感器通过晶圆级集成等技术集成在单个封装内,这属于SoC集成的范畴。目标专利的“低电力岛状物”是SoC中为低功耗操作设计的区域。虽然对比文件未明确使用“低电力岛状物”一词,但本领域技术人员基于对比文件对高密度集成和电力管理([0194])的公开,能够合理推断出:为了优化功耗,可以将通用处理器、MPU(融合引擎)、硬件缓冲区(伴随存储器)及其接口控制逻辑(外围控制器功能)集成在SoC的特定低功耗区域或域中。这是一种符合芯片设计常识的隐含公开。
**技术特征K:其中所述传感器融合引擎是始终接通子系统AOSS的部分。《未公开》**(对比文件全文中未提及“始终接通子系统(AOSS)”,也未描述传感器融合引擎是其一部分。)如特征I所述,对比文件不存在“始终接通子系统(AOSS)”这一概念。因此,将传感器融合引擎描述为AOSS的一部分的技术特征,在对比文件中没有任何依据,既未被直接公开,也无法通过合理推理隐含得出。

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