적응 필터
DSP System Toolbox™는 LMS 및 RLS 적응형 유한 임펄스 응답(FIR) 필터 알고리즘의 여러 변형을 제공합니다. 이러한 알고리즘은 세부적으로는 다르지만 적응 필터 출력과 원하는 신호 간 오차 차이를 최소화하는 일반적인 연산 방식을 공유합니다. MSE(평균제곱오차)는 이 오차를 수량화하는 데 가장 일반적으로 사용되는 메트릭입니다. 적응 필터는 음향 잡음 소거, 반향 소거, 빔 형성, 시스템 식별, 생체 의료 신호 향상, 통신 채널 이퀄라이제이션 등 여러 응용 분야에서 널리 사용됩니다. 이러한 응용 분야의 일부를 설명하는 예제는 System Identification of FIR Filter Using LMS Algorithm 항목, Noise Cancellation Using Sign-Data LMS Algorithm 항목, Inverse System Identification Using RLS Algorithm 항목을 참조하십시오.
입력이 채색된 경우 dsp.AffineProjectionFilter
객체에서 제공하는 아핀 투영 적응 필터 알고리즘이 LMS 변형에 비해 수렴 속도를 크게 개선합니다. 계산 비용이 증가되는 경우 dsp.AdaptiveLatticeFilter
객체에서 제공하는 적응 격자 필터 알고리즘을 사용하여 대응되는 LMS 및 RLS보다 더 좋은 수렴을 얻을 수 있습니다. dsp.FrequencyDomainAdaptiveFilter
객체를 사용하여 주파수 영역에서 적응 FIR 필터를 구현할 수도 있습니다.
수렴 성능은 실제 MSE(msesim
에 의해 결정됨)의 궤적과 이 궤적이 예측 MSE(msepred
에 의해 결정됨)에 어떻게 수렴하는지에 따라 결정됩니다.
객체
dsp.BlockLMSFilter | Compute output, error, and weights using block least mean squares (LMS) adaptive algorithm |
dsp.LMSFilter | Compute output, error, and weights of least mean squares (LMS) adaptive filter |
dsp.RLSFilter | Compute output, error and coefficients using recursive least squares (RLS) algorithm |
dsp.AffineProjectionFilter | Compute output, error and coefficients using affine projection (AP) Algorithm |
dsp.AdaptiveLatticeFilter | Adaptive lattice filter |
dsp.FastTransversalFilter | Fast transversal least-squares FIR adaptive filter |
dsp.FilteredXLMSFilter | Filtered XLMS filter |
dsp.FrequencyDomainAdaptiveFilter | Compute output, error, and coefficients using frequency-domain FIR adaptive filter |
블록
Block LMS Filter | Compute output, error, and weights using LMS adaptive algorithm |
Fast Block LMS Filter | Compute output, error, and weights using least mean squares (LMS) adaptive algorithm |
Frequency-Domain Adaptive Filter | Compute output, error, and coefficients using frequency domain FIR adaptive filter |
Kalman Filter | Predict or estimate states of dynamic systems |
LMS Filter | Compute output, error, and weights using least mean squares (LMS) adaptive algorithm |
LMS Update | Estimate weights of least mean squares (LMS) adaptive filter |
RLS Filter | Compute filtered output, filter error, and filter weights for given input and desired signal using RLS adaptive filter algorithm |
도움말 항목
- Overview of Adaptive Filters and Applications
General discussion on how adaptive filters work, list of adaptive filter algorithms in DSP System Toolbox, convergence performance, and details on few common applications.
- System Identification of FIR Filter Using LMS Algorithm
Identify an unknown system using LMS algorithm.
- System Identification of FIR Filter Using Normalized LMS Algorithm
Identify an unknown system using normalized LMS algorithm.
- Compare Convergence Performance Between LMS Algorithm and Normalized LMS Algorithm
Compare the speed with which the adaptive filter algorithms converge.
- Signal Enhancement Using LMS and NLMS Algorithms
Introduces adaptive filters through a signal enhancement application.
- Noise Cancellation Using Sign-Data LMS Algorithm
Perform noise cancellation using sign-data LMS algorithm.
- System Identification Using RLS Adaptive Filtering
This example shows how to use a recursive least-squares (RLS) filter to identify an unknown system modeled with a lowpass FIR filter.
- Inverse System Identification Using RLS Algorithm
Perform inverse system identification using dsp.RLSFilter.
- Compare RLS and LMS Adaptive Filter Algorithms
Comparison of RLS and LMS adaptive filter algorithms.
- Adapt Multiple Filters Using LMS Update Block
Adapt multiple filters independently using the same LMS Update block. Use the Adapt port of the LMS Update block to selectively enable or disable the filters from being adapted.
- Model Adaptive Linear Combiner using LMS Update Block
Use LMS Update block as an adaptive linear combiner.
- Remove Low Frequency Noise in Simulink Using Normalized LMS Adaptive Filter
Design a normalized LMS adaptive filter and use it to remove low frequency noise in Simulink®.
- Noise Cancellation in Simulink Using Normalized LMS Adaptive Filter
Remove colored noise generated from an acoustic environment, using a normalized LMS adaptive filter.
- Variable-Size Signal Support DSP System Objects
List of System objects that support variable-sized signals in DSP System Toolbox.