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 3):
The method of  claim 1 , wherein using the TFPF algorithm in the step c) comprises:\n by using the TFPF algorithm, processing the first signal-dominated mode component c 1 (n) to obtain a signal component s 1 (n) from which the random noise has been eliminated, and the processing comprising: 1). performing an edge data extension for the signal-dominated mode component c 1 (n) to obtain an extended signal c\u2032 1 (m), that is, c 1 \u2032 \ue8a0 ( m ) = { c 1 \ue8a0 ( 1 ) , 1 \u2264 m \u2264 p c 1 \ue8a0 ( m - p ) , p + 1 \u2264 m \u2264 p + N c 1 \ue8a0 ( N ) , p + N + 1 \u2264 m \u2264 2 \ue89e p + N where N is a length of the original observed signal, p is the number of data points extended at both ends; 2). scaling the extended signal c\u2032 1 (m): d 1 \u2032 \ue8a0 ( m ) = ( a - b ) \u00b7 c 1 \u2032 \ue8a0 ( m ) - min \ue8a0 [ c 1 \u2032 \ue8a0 ( m ) ] max \ue8a0 [ c 1 \u2032 \ue8a0 ( m ) ] - min \ue8a0 [ c 1 \u2032 \ue8a0 ( m ) ] + b where d\u2032 1 (m) is the scaled signal, the coefficients a and b are the maximum value and the minimum value of the scaled signal respectively, satisfying 0.5\u2265a=max[d\u2032 1 (m)], b=min[d\u2032 1 (m)]\u22650; 3). performing frequency modulation encoding on the scaled signal d\u2032 1 (m) to obtain an analytical signal of unit amplitude: z 1 \ue8a0 ( m ) = e j \ue89e \ue89e 2 \ue89e \ue89e \u03c0 \ue89e \u2211 \u03bb = 0 m \ue89e \ue89e d 1 \u2032 \ue8a0 ( \u03bb ) where z 1 (m) is the analytical signal obtained after the frequency modulation encoding; 4). performing Discrete Pseudo-Wigner-Ville Transform for the obtained analytical signal z 1 (m) to calculate a time-frequency distribution of z 1 (m): W z 1 \ue8a0 ( m , k ) = 2 \ue89e \u2211 l = - L L \ue89e \ue89e w \ue8a0 ( l ) \ue89e z 1 \ue8a0 ( m + l ) \ue89e z 1 * \ue8a0 ( m - l ) \ue89e e - j \ue89e \ue89e 4 \ue89e \ue89e \u03c0 \ue89e \ue89e kl where w(l) is a window function and its width is 2L+1; 5). taking the peak of W z i (m, k) as a valid estimate of the signal, that is:\n (m)=arg k max[ W z 1 ( m,k )] \n where arg k max[\u22c5] represents taking the maximum operator along frequency; 6). inverse-scaling the estimated value of the valid signal, and restoring the signal amplitude: \ue89e ( m ) = ( \u2032 \ue89e ( m ) - b ) \ue89e ( max \ue8a0 [ c 1 \u2032 \ue8a0 ( m ) ] - min \ue8a0 [ c 1 \u2032 \ue8a0 ( m ) ] ) a - b + min \ue8a0 [ c 1 \u2032 \ue8a0 ( m ) ] 7). removing the extended edge obtained after filtering, to obtain the signal component s 1 (n) from which the random noise has been eliminated:\n s 1 ( n )= ( n+p ), 1\u2264 n\u2264N  \n 8). processing the signal-dominated mode components c 2 (n), . . . , c j (n) sequentially in accordance with the above steps 1) to7), to obtain the signal components s 2 (n), . . . , s j (n) from which the random noise has been eliminated.

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): 0.4957511771584196
- 35 USC 102 Novelty (BERT): 0.4864778593080801
- Combined Prediction Score: 0.4948238453733856
- Mean Citation Score: 156.201542
- Max Citation Score: 159.62913999999995
- Similarity Product: 102.97709083052752

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