PATENT CLAIM ANALYSIS

Application Number: 15943852
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-04
Patent Classification: ["324", "613000"]

Abstract:
The instant invention relates to a method for noise reduction from a magnetic resonance sounding (MRS) oscillating signal, and more particularly, to a data processing method for reducing random noise contained in MRS oscillating signal based on joint algorithm principles of EMD and TFPF. A MRS oscillating signal is decomposed into different eigen-mode components by using decomposition characteristic of EMD algorithm; then a signal-dominated eigen-mode component is encoded as an instantaneous frequency of an analytical signal of unit amplitude using TFPF algorithm; and random noise is suppressed with the characteristics that the time-frequency distribution of the analytical signal is concentrated along with the instantaneous frequency. The method requires fewer filtering constraints and is simple to operate without need of designing a filtering interval in the time-frequency domain, and has good adaptability to the MRS oscillating signal with a low signal-noise-ratio.

Claim (Index 2):
The method of  claim 1 , wherein the EMD decomposition in the step a) uses EMD algorithm, comprising:\n first step, identifying all the maximum points and all the minimum points of the observed signal X(n), and performing a cubic spline interpolation for all the maximum points and all the minimum points respectively, to obtain an upper envelope curve E max (n)and a lower envelope curve E min (n)of the data; second step, calculating a corresponding average value of the upper and lower envelope curves to obtain a mean curve F 1 (n); F 1 \ue8a0 ( n ) = E max \ue8a0 ( n ) + E min \ue8a0 ( n ) 2 third step, subtracting the average value F 1 (n) from the observed signal X(n) to obtain a detail component H 1 (n), and determining whether the detail component is an eigen-mode function on condition that: {circle around (1)}. a mean of the function is zero; the function is local symmetry, and the number of zero-crossing points and the number of extreme points are the same or differ at most by one; and {circle around (2)}. the sum of the upper and lower envelope values of the function is always zero at any time; if the conditions are not satisfied, repeating the first and second steps for H 1 (n) until satisfying the conditions, and obtaining a first eigen-mode component C 1 (n); fourth step, subtracting the first eigen-mode component C 1 (n) from the observed signal X(n) to obtain an amount of residual R 1 (n), that is:\n X ( n )\u2212 C 1 ( n )= R 1 ( n ) \n repeating the first, second and third steps for the amount of residual R 1 (n) as a new signal to be processed, for continuous screening signal; until obtaining a second eigen-mode component C 2 (n), and so on, obtaining i different eigen-mode components C 1 (n), . . . , C i (n) and one trend item R i (n):\n R 1 ( n )\u2212 C 2 ( n )= R 2 ( n ) , . . . ,  R i\u22121 ( n )\u2212 C i ( n )= R i ( n ) \n X ( n )= C 1 ( n )+ . . . + C i ( n )+ R i ( n );

Metadata:
- Claim Count in Document: 5.0
- Percentile: 91.0
- Lexical Diversity: 1.74419
- Patent Class: 324.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15426760', '11490078', '09267968', '15519311', '13813138']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4988647484313583
- 35 USC 102 Novelty (BERT): 0.4747452767943974
- Combined Prediction Score: 0.4964528012676622
- Mean Citation Score: 156.201542
- Max Citation Score: 159.62913999999995
- Similarity Product: 114.3507180539882

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test