Sampled Data Compression by Second-Derivative Point Selection
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Solution Overview
Problem
Current data compression techniques for sampled data, such as aperture sampling, do not provide sufficient compression for the increasing amounts of media content generated by electronic devices, leading to excessive storage space consumption and increased bandwidth and transmission time requirements.
Innovation Solution
An electronic device with a processing element and memory element that analyzes the slopes of sampled data points, calculating differences and difference changes, and stores data points only when the difference change exceeds a threshold, thereby compressing the data effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional aperture sampling compression techniques are used, then some data reduction is achieved, but the compression ratio is insufficient for the increasing amounts of media content
Solution Approach 1:
The patent changes the parameter being analyzed from first derivative (slope) to second derivative (rate of change of slope). By detecting points where the second derivative exceeds a threshold, the system identifies significant inflection points in the signal, achieving higher compression ratios while maintaining signal reconstruction quality
Solution Approach 2:
The patent performs preliminary analysis of the sampled data by calculating differences and difference changes before final storage. This pre-processing identifies which data points are critical for signal reconstruction, allowing the system to store only essential points and achieve better compression
2Reliability
If more sampled data is stored to maintain signal reconstruction quality, then reconstruction accuracy is preserved, but storage space requirements increase
Solution Approach 1:
By shifting from first to second derivative analysis, the patent identifies a more selective subset of critical data points. The second derivative thresholding method captures only the most significant signal features, maintaining reconstruction quality while reducing the number of stored points
Solution Approach 2:
The patent extracts only the essential data points needed for signal reconstruction by applying a second derivative threshold. This selective extraction removes redundant information while preserving the critical features necessary for accurate signal recovery
Data Source
AI summary
An electronic device for compressing sampled data comprises a memory element and a processing element. The memory element is configured to store sampled data points and sampled times. The processing element is in electronic communication with the memory element and is configured to receive a plurality of sampled data points, a slope for each sampled data point in succession, the slope being a value of a change between the sampled data point and its successive sampled data point, and store the sampled data point in the memory element when the slope changes in value from a previous sampled data point.