# Tagged Questions

An adaptive filter is a filter that self-adjusts its transfer function according to an optimization algorithm driven by an error signal.

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Adaptive IIR filters is not straightforward, and may be unstable. Many people say that adaptive IIR filters use less coefficients than FIR filters. What I'm curious about is how many coefficients can ...
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I'm trying to implement a RLS adaptive filter in MATLAB and simulink. This is the Simulink diagram. and code in RLS_Filter looks like this: ...
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### “Desired signal” in LMS adaptive filters?

I'm trying to understand how to specify the "desired signal" in adaptive LMS filters such as the following: This one, or this one page 7, or this one. It seems like the example there uses it for ...
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### Instability problem in NLMS adaptive algorithm

I have been used NLMS algorithm to equalize 4x4 MIMO signals, but the bit-error-rate (BER) after equalization is unstable with iterations. I don't know if it is the normal behavior of the adaptive ...
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### Adaptive filter with two inputs

I have general theoretical questions: Is it true that an adaptive filter with two inputs (one normal and one delayed by the single time increment) can completely get rid of any single frequency ...
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### LMS filter weight update

I have a general question regarding Least mean squares adaptive filters. Using the example of noise cancellation, I understand that if you have a set of reference signals (S) and corrupted signals (S+...
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### What criteria should be used for smoothing

Actually I have some measurement which I want to get rid of noise I want to use different filter techniques but I am wondering what criteria I should use to check if I am removing noise or not or if ...
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### Adaptive LMS(Least Mean Square) Equalization in OFDM

I have a problem with the adaptive LMS frequency domain equalization in OFDM. When I assume that the receiver knows the channel perfectly and apply zero forcing equalizer, there is no problem. Also ...
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### Are the RLS filter and Kalman filter gradient methods?

I would like to extend my previous question What is difference between LMS and gradient-descent adaptation? with this other question. I found out, that RLS and Kalman filter learning seems to be ...
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### Removing low frequency vibrations from measured signal

Suppose I have two sensors $s_1$ and $s_2$. $s_1$ measures the desired heart signal (with most of the frequency content below 100 Hz), and the other is a reference sensor picking mainly background ...
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### Kalman for 3D position and 1D orientation

Is the following state correct for a Constant Acceleration (CA) model KF applied for tracking an object which moves in (x, y, z) and have the freedom of rotation $\phi$ around the $z$ axis? \begin{...
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I found algorithms that seems the same to me, but they are described with different names (in field of adaptive filtering). For example: LMS - least-mean-squares seems to be GD - stochastic ...
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### Best DSP algoritms for ultrasonic background noise cancellation

I am looking into detection of pressurized gas leaks by means of the broadband hissing sound (white noise) generated from pressurized leaking gas. The instrument will have a broadband microphone ...
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### What is an Adaptive Mean Filter?

$$\hat f(x, y) = g(x, y)-\frac{\sigma_n^2}{\sigma_L^2}\left[g(x, y)-m_L\right]$$ What are the meanings of the following terms: $m_L$ ${\sigma_\eta}^2$ ${\sigma_L}^2$ Here we see that $m_L$ is ...
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### RLS Algorithm Convergence

I am looking for some help to understand the concept how RLS converges? If possible to present it graphically that would be best. It is very easy to understand the understanding of convergence in case ...
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### How do you select an optimal adaptive filter length?

Is it a trial and error process or can you observe the minimum number of taps after which the impulse response reaches a steady state?
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### How is it determined that an adaptive filter has converged?

Is it when the cost function such as the error signal or Mean Square Error (MSE) signal is minimised?
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### Eigenvalues of a vector

I'm trying to calculate (with Matlab) the minimal and maximal Eigenvalues $\lambda_{min}$ and $\lambda_{max}$ of the autocorrelationmatrix $R$ to adjust the stepsize of an adaptive filter. My input ...
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I have designed an adaptive filter for noise cancellation. Is there any standard way of testing adaptive filters?
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### How many samples per cycle(time period) is actually enough to reproduce the sine wave sound properly?

I have been working on Active Noise Cancellation in real time for Air vent in kitchen. Initially for the demonstration purpose, I am using sinusoidal sound ( 40k Hz Fs,1000 samples, 2 kHz frequency, 1 ...
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### Terminologies: Adaptive, recursive and iterative

Considering non-linear filtering technique like Extended Kalman filtering with Expectation Maximization (EM). EM is an iterative technique but what is Kalman filtering? Is Kalman Filtering called ...
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### Echo cancellation supporting long delays and without frequency domain processing

AEC algorithms mostly rely on LMS adaptive filtering, i.e. you update FIR filter coefficients then perform the filtering. Theoretically, the FIR must be as long as the maximum echo length you want to ...
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### LMS adaptive filter relatively delayed signal and reference inputs

I'm using two microcontrollers to implement an adaptive LMS filter to filter out the noise from the signal. One is recording the noise and streaming the data to the other microcontroller which is ...
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### Audio block-processing discontinuities

I have an algorithm that looks at an audio frame, calculates a threshold in db-rms, and decides to filter the frame whether or not the threshold is crossed. However, filtering each block is producing ...
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### FIR adaptive filter without reference input

Now I am trying to design FIR adaptive filter for unknown frequency CW rejection. I've already read many books or paper about 'adaptive noise canceling'. However I couldn't find any information for ...
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### Help in deriving the update rule for equalizer

Considering an FIR system excited by an input $s_n$. If the input is derived from a mapping, and a +1/-1 BPSK signal is derived. Considering the Constant Modulus Algorithm (CMA). The channel is ...
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### MATLAB : Proper estimation of weights and how to calculate MSE for QPSK signal for Constant Modulus Algorithm

I had asked conceptual Question about Constant Modulus Algorithm. I am implementing the simple steps of the algorithm, as I do not have the cma() built in module. ...
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The quadratic performance surface of an adaptive filter is a paraboloid. Its minimum can be found wherever the gradient is zero. However, since there are two types of paraboloids (elliptical and ...
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### Motion artifact cancellation from ECG signal using 3-axis accelerometer data

I have a ECG signal measured as a test subject is performing 3 different activities - sitting, walking(2mph) and jogging(5mph) and also the corresponding 3-axis accelerometer(X,Y and Z) signals. I can ...
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### Adaptive Digital Filter Block Diagram Question

I'm currently attempting to study up on adaptive digital filters. My book presents the diagram I've included below and I'm having trouble understanding conceptually what it's indicating. The problem ...
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### Unit delay operator as parameter in function

I'm busy trying to implement a filter from this paper. I'm a bit confused with one particular step (30e in the paper). Basically I need to find the zero frequency gain (K) of the following whitening/...
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### Image Processing: Flatten a 3D Ball

There are many descriptions of how to turn a 2D image into a 3D one, however I want to do the opposite, in particular to a ball. As an example, consider the following ball: If only the (relatively) ...
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### Correlating accelerometer data

I am getting a signal from a device. This signal contains a non-random noise signal in it. I want to remove that noise from the signal. This noise is correlated to the motion the device is having. So ...
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### Deep zeros in the spectrum of the input data?

I wanted to know the meaning of "deep zeros" in the spectrum of the input data. I came across this terminology while going through the introduction of chapter 2 (Bussgang techniques for blind ...