On-the-Fly Sensor Data Projection With Matrix Decomposition
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Solution Overview
Problem
Conventional data acquisition systems face challenges in processing images on the fly due to high memory and calculation resource requirements for projecting images into a different representation domain, which is problematic for real-time applications.
Innovation Solution
The system employs a processing device that projects sensor data using a matrix decomposition method, specifically decomposing the projection matrix into A, B, and S matrices, allowing for on-the-fly processing by cascaded stages synchronized with a clock signal, reducing memory needs and enabling efficient projection of images into a lower-dimensional representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image projection is performed using a conventional transition matrix, then the projection accuracy is maintained, but the memory and calculation resource requirements become excessively high for real-time processing
Solution Approach 1:
The patent segments the projection operation into three distinct stages: (1) multiplying sensor data by diagonal matrix B to obtain intermediate results, (2) multiplying by matrix A to obtain further intermediate results, and (3) integrating by summing contributions from all pixel subsets. This segmentation allows each stage to be processed independently with reduced memory requirements, enabling real-time processing while maintaining projection accuracy.
Solution Approach 2:
The patent performs preliminary grouping of pixels into subsets before projection, organizing the data structure in advance to facilitate efficient processing. By pre-organizing pixels into subsets and calculating their contributions separately, the system prepares data in a format that minimizes subsequent computation complexity and memory access requirements during the actual projection operation.
2Measurement precision
If complete image data is stored before processing, then accurate projection is achieved, but the memory storage requirements increase significantly
Solution Approach 1:
The patent divides the complete image into multiple pixel subsets and processes each subset independently through the projection stages. Instead of storing and processing the entire image simultaneously, the system processes subsets sequentially, accumulating results through integration. This reduces peak memory requirements from storing the complete image to storing only subset-sized data structures.
Solution Approach 2:
The system performs preliminary organization of pixels into subsets and pre-calculates certain transformation parameters before the actual projection. This preliminary structuring of data allows the system to work with smaller, organized subsets rather than the complete unstructured image data, reducing memory requirements while preserving the ability to achieve accurate projection through the staged processing approach.
3Productivity
If on-the-fly processing is implemented, then real-time processing capability is achieved, but the processing complexity increases
Solution Approach 1:
The patent implements on-the-fly processing by segmenting the projection operation into three computationally manageable stages that can be executed sequentially for each pixel subset. This segmentation transforms a single complex projection operation into multiple simpler operations that can be performed incrementally as data arrives, enabling real-time processing without requiring the entire dataset to be available beforehand.
Solution Approach 2:
The system performs preliminary organization of incoming sensor data into pixel subsets and pre-prepares the transformation matrices (A and B) before projection. This preliminary structuring of both data and transformation parameters reduces the computational complexity during the actual on-the-fly processing, allowing real-time operation while maintaining manageable processing complexity through advance preparation of data structures.
Data Source
AI summary
An electronic system including: a sensor (201) capable of successively supplying n vectors L.sub.i each including k values L.sub.i(j); and an electronic device (403) for processing on the fly the values measured by the sensor, including: a first stage (407) capable, each time a vector L.sub.i has been supplied by the sensor, of multiplying the k values L.sub.i(j) of vector L.sub.i by respectively k coefficients b.sub.i(j), and of supplying a vector T1.sub.i of k values T1.sub.i(j); a second stage (409) capable, each time a vector T1.sub.i has been supplied, of multiplying vector T1.sub.i by a matrix of k*p coefficients, and of supplying a vector T2.sub.i of p values T2.sub.i(l); and a third stage (411) capable of digitally integrating the n vectors T2.sub.i and of supplying an output vector IT of p values IT(l).