Data processing: structural design – modeling – simulation – and em – Emulation – Compatibility emulation
Reexamination Certificate
1999-11-05
2003-05-13
Frejd, Russell (Department: 2123)
Data processing: structural design, modeling, simulation, and em
Emulation
Compatibility emulation
C703S002000, C703S014000, C706S025000, C706S045000, C708S322000, C348S171000
Reexamination Certificate
active
06564180
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to data processing apparatuses and data processing methods, and more particularly, to a data processing apparatus and a data processing method which allow noise included in data to be removed more effectively.
2. Description of the Related Art
In general, data such as transmitted or reproduced image data and sound data includes noise which changes as time elapses. To remove the noise included in the data, there have been known methods in which the average, namely, the whole average, of the whole input data is obtained and in which the average of a part of the input data, which is called a moving average, is obtained.
The method in which the whole average is calculated is effective when the degree of noise included in data, namely, the signal-to-noise ratio (S/N ratio) of the data, is uniform. When the S/N ratio of data varies, however, a portion of the data having a low S/N ratio affects a portion of the data having a high S/N ratio to make it difficult to remove the noise effectively in some cases.
In the method in which the moving average is calculated, since the average of data positioned close to the current input data in the time domain is obtained, the processing result is affected by a change in the S/N ratio of the data. In other words, the processing result has a high S/N ratio for a portion of the data having a high S/N ratio, but the processing result has a low S/N ratio for a portion of the data having a low S/N ratio.
SUMMARY OF THE INVENTION
Accordingly, it is an object of the present invention to solve the foregoing drawbacks.
The foregoing object is achieved in one aspect of the present invention through the provision of a data processing apparatus for processing input data and outputting the processed data as output data, including a first processing section which includes a real-time learning section for learning in real time a processing method by which the input data and the output data corresponding to the input data are evaluated and the input data is processed according to the evaluation such that the output data is improved as time elapses, and a data processing section for adaptively processing the input data according to the processing method learned by the real-time learning section and outputting the output data; and a second processing section for processing preceding input data which has been input in time prior to focused input data which is processed by the first processing section, according to the focused output data corresponding to the focused input data and the evaluation of the focused output data to output the preceding output data corresponding to the preceding input data.
The foregoing object is achieved in another aspect of the present invention through the provision of a data processing method for processing input data and outputting the processed data as output data, including a first processing step which includes a real-time learning step for learning in real time a processing method by which the input data and the output data corresponding to the input data are evaluated and the input data is processed according to the evaluation such that the output data is improved as time elapses, and a data processing step for adaptively processing the input data according to the processing method learned by the real-time learning step and outputting the output data; and a second processing step for processing preceding input data which has been input in time prior to focused input data which is processed by the first processing step, according to the focused output data corresponding to the focused input data and the evaluation of the focused output data to output the preceding output data corresponding to the preceding input data.
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Ando Kazutaka
Kobayashi Naoki
Kondo Tetsujiro
Frejd Russell
Frommer William S.
Frommer & Lawrence & Haug LLP
Phan Thai
Simon Darren M.
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