diff --git a/src/UnitTests/IntegralTransformsTests/FourierTest.cs b/src/UnitTests/IntegralTransformsTests/FourierTest.cs
index e628f971..afbc6d8a 100644
--- a/src/UnitTests/IntegralTransformsTests/FourierTest.cs
+++ b/src/UnitTests/IntegralTransformsTests/FourierTest.cs
@@ -43,7 +43,13 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         /// <summary>
         /// Continuous uniform distribution.
         /// </summary>
-        private readonly IContinuousDistribution _uniform = new ContinuousUniform(-1, 1);
+        private IContinuousDistribution GetUniform(int seed)
+        {
+            return new ContinuousUniform(-1, 1)
+            {
+                RandomSource = new Random(seed)
+            };
+        }
 
         /// <summary>
         /// Naive transforms real sine correctly.
@@ -87,7 +93,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         [Test]
         public void Radix2ThrowsWhenNotPowerOfTwo()
         {
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x7F);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), 0x7F);
 
             var dft = new DiscreteFourierTransform();
 
diff --git a/src/UnitTests/IntegralTransformsTests/HartleyTest.cs b/src/UnitTests/IntegralTransformsTests/HartleyTest.cs
index 7a1b571f..b21dfe45 100644
--- a/src/UnitTests/IntegralTransformsTests/HartleyTest.cs
+++ b/src/UnitTests/IntegralTransformsTests/HartleyTest.cs
@@ -43,7 +43,13 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         /// <summary>
         /// Continuous uniform distribution.
         /// </summary>
-        private readonly IContinuousDistribution _uniform = new ContinuousUniform(-1, 1);
+        private IContinuousDistribution GetUniform(int seed)
+        {
+            return new ContinuousUniform(-1, 1)
+            {
+                RandomSource = new Random(seed)
+            };
+        }
 
         /// <summary>
         /// Verify if matches DFT.
@@ -80,7 +86,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         public void NaiveMatchesDft(HartleyOptions hartleyOptions, FourierOptions fourierOptions)
         {
             var dht = new DiscreteHartleyTransform();
-            var samples = SignalGenerator.Random(x => x, _uniform, 0x80);
+            var samples = SignalGenerator.Random(x => x, GetUniform(1), 0x80);
 
             VerifyMatchesDft(
                 samples,
diff --git a/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs b/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs
index 54970389..0f9f23dc 100644
--- a/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs
+++ b/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs
@@ -43,7 +43,13 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         /// <summary>
         /// Continuous uniform distribution.
         /// </summary>
-        private readonly IContinuousDistribution _uniform = new ContinuousUniform(-1, 1);
+        private IContinuousDistribution GetUniform(int seed)
+        {
+            return new ContinuousUniform(-1, 1)
+                {
+                    RandomSource = new Random(seed)
+                };
+        }
 
         /// <summary>
         /// Verify if is reversible complex.
@@ -58,7 +64,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
             Func<Complex[], Complex[]> forward,
             Func<Complex[], Complex[]> inverse)
         {
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, count);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), count);
             var work = new Complex[samples.Length];
             samples.CopyTo(work, 0);
 
@@ -84,7 +90,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
             Func<double[], double[]> forward,
             Func<double[], double[]> inverse)
         {
-            var samples = SignalGenerator.Random(x => x, _uniform, count);
+            var samples = SignalGenerator.Random(x => x, GetUniform(1), count);
             var work = new double[samples.Length];
             samples.CopyTo(work, 0);
 
@@ -187,7 +193,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         [Test]
         public void FourierDefaultTransformIsReversible()
         {
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x7FFF);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), 0x7FFF);
             var work = new Complex[samples.Length];
             samples.CopyTo(work, 0);
 
diff --git a/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs b/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs
index bb943024..6f3aac6c 100644
--- a/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs
+++ b/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs
@@ -43,7 +43,13 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         /// <summary>
         /// Continuous uniform distribution.
         /// </summary>
-        private readonly IContinuousDistribution _uniform = new ContinuousUniform(-1, 1);
+        private IContinuousDistribution GetUniform(int seed)
+        {
+            return new ContinuousUniform(-1, 1)
+            {
+                RandomSource = new Random(seed)
+            };
+        }
 
         /// <summary>
         /// Verify matches naive complex.
@@ -102,7 +108,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         public void FourierRadix2MatchesNaiveOnRandom(FourierOptions options)
         {
             var dft = new DiscreteFourierTransform();
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x80);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), 0x80);
 
             VerifyMatchesNaiveComplex(
                 samples,
@@ -152,7 +158,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         public void FourierBluesteinMatchesNaiveOnRandomPowerOfTwo(FourierOptions options)
         {
             var dft = new DiscreteFourierTransform();
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x80);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), 0x80);
 
             VerifyMatchesNaiveComplex(
                 samples,
@@ -177,7 +183,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         public void FourierBluesteinMatchesNaiveOnRandomNonPowerOfTwo(FourierOptions options)
         {
             var dft = new DiscreteFourierTransform();
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x7F);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), 0x7F);
 
             VerifyMatchesNaiveComplex(
                 samples,
diff --git a/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs b/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs
index 6f6ca0ac..719eff93 100644
--- a/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs
+++ b/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs
@@ -44,7 +44,13 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         /// <summary>
         /// Continuous uniform distribution.
         /// </summary>
-        private readonly IContinuousDistribution _uniform = new ContinuousUniform(-1, 1);
+        private IContinuousDistribution GetUniform(int seed)
+        {
+            return new ContinuousUniform(-1, 1)
+            {
+                RandomSource = new System.Random(seed)
+            };
+        }
 
         /// <summary>
         /// Fourier default transform satisfies parsevals theorem.
@@ -54,7 +60,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         [TestCase(0x7FF)]
         public void FourierDefaultTransformSatisfiesParsevalsTheorem(int count)
         {
-            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, count);
+            var samples = SignalGenerator.Random((u, v) => new Complex(u, v), GetUniform(1), count);
 
             var timeSpaceEnergy = (from s in samples select s.MagnitudeSquared()).Mean();
 
@@ -77,7 +83,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
         [TestCase(0x1F)]
         public void HartleyDefaultNaiveSatisfiesParsevalsTheorem(int count)
         {
-            var samples = SignalGenerator.Random(x => x, _uniform, count);
+            var samples = SignalGenerator.Random(x => x, GetUniform(1), count);
 
             var timeSpaceEnergy = (from s in samples select s * s).Mean();